nips2019.md

NIPS2019 Paper List

论文	作者	摘要	代码	引用数
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation	Risto Vuorio, ShaoHua Sun, Hexiang Hu, Joseph J. Lim		code	-1
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks	Jiasen Lu, Dhruv Batra, Devi Parikh, Stefan Lee		code	-1
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers	Liwei Wu, Shuqing Li, ChoJui Hsieh, James L. Sharpnack		code	-1
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video	Jiawang Bian, Zhichao Li, Naiyan Wang, Huangying Zhan, Chunhua Shen, MingMing Cheng, Ian D. Reid		code	-1
Zero-shot Learning via Simultaneous Generating and Learning	Hyeonwoo Yu, Beomhee Lee		code	-1
Ask not what AI can do, but what AI should do: Towards a framework of task delegability	Brian Lubars, Chenhao Tan		code	-1
Stand-Alone Self-Attention in Vision Models	Niki Parmar, Prajit Ramachandran, Ashish Vaswani, Irwan Bello, Anselm Levskaya		code	-1
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks	Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V. Le, Honglak Lee		code	-1
Unsupervised learning of object structure and dynamics from videos	Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin P. Murphy, Honglak Lee		code	-1
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism	Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Xu Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Yonghui Wu, Zhifeng Chen		code	-1
Meta-Learning with Implicit Gradients	Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine		code	-1
Adversarial Examples Are Not Bugs, They Are Features	Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry		code	-1
Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks	Vineet Kosaraju, Amir Sadeghian, Roberto MartínMartín, Ian D. Reid, Hamid Rezatofighi, Silvio Savarese		code	-1
FreeAnchor: Learning to Match Anchors for Visual Object Detection	Xiaosong Zhang, Fang Wan, Chang Liu, Rongrong Ji, Qixiang Ye		code	-1
Private Hypothesis Selection	Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu		code	-1
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians	Gautam Kamath, Or Sheffet, Vikrant Singhal, Jonathan R. Ullman		code	-1
Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation	Mark Bun, Thomas Steinke		code	-1
Multi-Resolution Weak Supervision for Sequential Data	Paroma Varma, Frederic Sala, Shiori Sagawa, Jason Alan Fries, Daniel Y. Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré		code	-1
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision	Duc Tam Nguyen, Maximilian Dax, Chaithanya Kumar Mummadi, ThiPhuongNhung Ngo, Thi Hoai Phuong Nguyen, Zhongyu Lou, Thomas Brox		code	-1
The Point Where Reality Meets Fantasy: Mixed Adversarial Generators for Image Splice Detection	Vladimir V. Kniaz, Vladimir A. Knyaz, Fabio Remondino		code	-1
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle	Dinghuai Zhang, Tianyuan Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong		code	-1
Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement	Chao Yang, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu, Junzhou Huang, Chuang Gan		code	-1
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance	Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau		code	-1
Generalized Sliced Wasserstein Distances	Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde		code	-1
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise	Thanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard		code	-1
Blind Super-Resolution Kernel Estimation using an Internal-GAN	Sefi BellKligler, Assaf Shocher, Michal Irani		code	-1
Noise-tolerant fair classification	Alexandre Louis Lamy, Ziyuan Zhong		code	-1
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection	Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou		code	-1
Joint-task Self-supervised Learning for Temporal Correspondence	Xueting Li, Sifei Liu, Shalini De Mello, Xiaolong Wang, Jan Kautz, MingHsuan Yang		code	-1
Provable Gradient Variance Guarantees for Black-Box Variational Inference	Justin Domke		code	-1
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation	Justin Domke, Daniel Sheldon		code	-1
Experience Replay for Continual Learning	David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Gregory Wayne		code	-1
Deep ReLU Networks Have Surprisingly Few Activation Patterns	Boris Hanin, David Rolnick		code	-1
Chasing Ghosts: Instruction Following as Bayesian State Tracking	Peter Anderson, Ayush Shrivastava, Devi Parikh, Dhruv Batra, Stefan Lee		code	-1
Block Coordinate Regularization by Denoising	Yu Sun, Jiaming Liu, Ulugbek Kamilov		code	-1
Reducing Noise in GAN Training with Variance Reduced Extragradient	Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon LacosteJulien		code	-1
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries	Zihan Li, Matthias Fresacher, Jonathan Scarlett		code	-1
A Primal-Dual link between GANs and Autoencoders	Hisham Husain, Richard Nock, Robert C. Williamson		code	-1
muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking	Congchao Wang, Yizhi Wang, Yinxue Wang, ChiungTing Wu, Guoqiang Yu		code	-1
Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation	Qiming Zhang, Jing Zhang, Wei Liu, Dacheng Tao		code	-1
Invert to Learn to Invert	Patrick Putzky, Max Welling		code	-1
Equitable Stable Matchings in Quadratic Time	Nikolaos Tziavelis, Ioannis Giannakopoulos, Katerina Doka, Nectarios Koziris, Panagiotis Karras		code	-1
Zero-Shot Semantic Segmentation	Maxime Bucher, TuanHung Vu, Matthieu Cord, Patrick Pérez		code	-1
Metric Learning for Adversarial Robustness	Chengzhi Mao, Ziyuan Zhong, Junfeng Yang, Carl Vondrick, Baishakhi Ray		code	-1
DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction	Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomír Mech, Ulrich Neumann		code	-1
Batched Multi-armed Bandits Problem	Zijun Gao, Yanjun Han, Zhimei Ren, Zhengqing Zhou		code	-1
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning	FanYun Sun, Meng Qu, Jordan Hoffmann, ChinWei Huang, Jian Tang		code	-1
Differentially Private Bayesian Linear Regression	Garrett Bernstein, Daniel Sheldon		code	-1
Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos	Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu		code	-1
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling	Bichuan Guo, Yuxing Han, Jiangtao Wen		code	-1
CPM-Nets: Cross Partial Multi-View Networks	Changqing Zhang, Zongbo Han, Yajie Cui, Huazhu Fu, Joey Tianyi Zhou, Qinghua Hu		code	-1
Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis	Xihui Liu, Guojun Yin, Jing Shao, Xiaogang Wang, Hongsheng Li		code	-1
Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling	Andrey Kolobov, Yuval Peres, Cheng Lu, Eric Horvitz		code	-1
SySCD: A System-Aware Parallel Coordinate Descent Algorithm	Nikolas Ioannou, Celestine MendlerDünner, Thomas P. Parnell		code	-1
Importance Weighted Hierarchical Variational Inference	Artem Sobolev, Dmitry P. Vetrov		code	-1
RSN: Randomized Subspace Newton	Robert M. Gower, Dmitry Kovalev, Felix Lieder, Peter Richtárik		code	-1
Trust Region-Guided Proximal Policy Optimization	Yuhui Wang, Hao He, Xiaoyang Tan, Yaozhong Gan		code	-1
Adversarial Self-Defense for Cycle-Consistent GANs	Dina Bashkirova, Ben Usman, Kate Saenko		code	-1
Towards closing the gap between the theory and practice of SVRG	Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis R. Bach, Robert M. Gower		code	-1
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control	Armin Lederer, Jonas Umlauft, Sandra Hirche		code	-1
ETNet: Error Transition Network for Arbitrary Style Transfer	Chunjin Song, Zhijie Wu, Yang Zhou, Minglun Gong, Hui Huang		code	-1
No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms	Max Vladymyrov		code	-1
Deep Equilibrium Models	Shaojie Bai, J. Zico Kolter, Vladlen Koltun		code	-1
Saccader: Improving Accuracy of Hard Attention Models for Vision	Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le		code	-1
Multiway clustering via tensor block models	Miaoyan Wang, Yuchen Zeng		code	-1
Regret Minimization for Reinforcement Learning with Vectorial Feedback and Complex Objectives	Wang Chi Cheung		code	-1
NAT: Neural Architecture Transformer for Accurate and Compact Architectures	Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang		code	-1
Selecting Optimal Decisions via Distributionally Robust Nearest-Neighbor Regression	Ruidi Chen, Ioannis Ch. Paschalidis		code	-1
Network Pruning via Transformable Architecture Search	Xuanyi Dong, Yi Yang		code	-1
Differentiable Cloth Simulation for Inverse Problems	Junbang Liang, Ming C. Lin, Vladlen Koltun		code	-1
Poisson-Randomized Gamma Dynamical Systems	Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna M. Wallach		code	-1
Volumetric Correspondence Networks for Optical Flow	Gengshan Yang, Deva Ramanan		code	-1
Learning Conditional Deformable Templates with Convolutional Networks	Adrian V. Dalca, Marianne Rakic, John V. Guttag, Mert R. Sabuncu		code	-1
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data	Han Liu, Zhizhong Han, YuShen Liu, Ming Gu		code	-1
Efficient Symmetric Norm Regression via Linear Sketching	Zhao Song, Ruosong Wang, Lin F. Yang, Hongyang Zhang, Peilin Zhong		code	-1
RUBi: Reducing Unimodal Biases for Visual Question Answering	Rémi Cadène, Corentin Dancette, Hédi BenYounes, Matthieu Cord, Devi Parikh		code	-1
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition	Jinwoo Choi, Chen Gao, Joseph C. E. Messou, JiaBin Huang		code	-1
NeurVPS: Neural Vanishing Point Scanning via Conic Convolution	Yichao Zhou, Haozhi Qi, Jingwei Huang, Yi Ma		code	-1
DATA: Differentiable ArchiTecture Approximation	Jianlong Chang, Xinbang Zhang, Yiwen Guo, Gaofeng Meng, Shiming Xiang, Chunhong Pan		code	-1
Learn, Imagine and Create: Text-to-Image Generation from Prior Knowledge	Tingting Qiao, Jing Zhang, Duanqing Xu, Dacheng Tao		code	-1
Memory-oriented Decoder for Light Field Salient Object Detection	Miao Zhang, Jingjing Li, Ji Wei, Yongri Piao, Huchuan Lu		code	-1
Multi-label Co-regularization for Semi-supervised Facial Action Unit Recognition	Xuesong Niu, Hu Han, Shiguang Shan, Xilin Chen		code	-1
Correlated Uncertainty for Learning Dense Correspondences from Noisy Labels	Natalia Neverova, David Novotný, Andrea Vedaldi		code	-1
Powerset Convolutional Neural Networks	Chris Wendler, Markus Püschel, Dan Alistarh		code	-1
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer	Arsenii Vanunts, Alexey Drutsa		code	-1
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums	Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié		code	-1
Point-Voxel CNN for Efficient 3D Deep Learning	Zhijian Liu, Haotian Tang, Yujun Lin, Song Han		code	-1
Deep Learning without Weight Transport	Mohamed Akrout, Collin Wilson, Peter C. Humphreys, Timothy P. Lillicrap, Douglas B. Tweed		code	-1
Combinatorial Bandits with Relative Feedback	Aadirupa Saha, Aditya Gopalan		code	-1
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme	Tao Sun, Yuejiao Sun, Dongsheng Li, Qing Liao		code	-1
A Condition Number for Joint Optimization of Cycle-Consistent Networks	Leonidas J. Guibas, Qixing Huang, Zhenxiao Liang		code	-1
Explicit Disentanglement of Appearance and Perspective in Generative Models	Nicki Skafte Detlefsen, Søren Hauberg		code	-1
Polynomial Cost of Adaptation for X-Armed Bandits	Hédi Hadiji		code	-1
Learning to Propagate for Graph Meta-Learning	Lu Liu, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang		code	-1
Secretary Ranking with Minimal Inversions	Sepehr Assadi, Eric Balkanski, Renato Paes Leme		code	-1
Nonparametric Regressive Point Processes Based on Conditional Gaussian Processes	Siqi Liu, Milos Hauskrecht		code	-1
Learning Perceptual Inference by Contrasting	Chi Zhang, Baoxiong Jia, Feng Gao, Yixin Zhu, Hongjing Lu, SongChun Zhu		code	-1
Selecting the independent coordinates of manifolds with large aspect ratios	YuChia Chen, Marina Meila		code	-1
Region-specific Diffeomorphic Metric Mapping	Zhengyang Shen, FrançoisXavier Vialard, Marc Niethammer		code	-1
Deep Supervised Summarization: Algorithm and Application to Learning Instructions	Chengguang Xu, Ehsan Elhamifar		code	-1
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations	Vincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein		code	-1
Reconciling λ-Returns with Experience Replay	Brett Daley, Christopher Amato		code	-1
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence	Fengxiang He, Tongliang Liu, Dacheng Tao		code	-1
Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs	Max Simchowitz, Kevin G. Jamieson		code	-1
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation	Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe, Takuya Akiba, Masanori Koyama		code	-1
Combinatorial Inference against Label Noise	Paul Hongsuck Seo, Geeho Kim, Bohyung Han		code	-1
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning	Chao Qu, Shie Mannor, Huan Xu, Yuan Qi, Le Song, Junwu Xiong		code	-1
Convolution with even-sized kernels and symmetric padding	Shuang Wu, Guanrui Wang, Pei Tang, Feng Chen, Luping Shi		code	-1
On The Classification-Distortion-Perception Tradeoff	Dong Liu, Haochen Zhang, Zhiwei Xiong		code	-1
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up	Dominic Richards, Patrick Rebeschini		code	-1
Online sampling from log-concave distributions	Holden Lee, Oren Mangoubi, Nisheeth K. Vishnoi		code	-1
Envy-Free Classification	MariaFlorina Balcan, Travis Dick, Ritesh Noothigattu, Ariel D. Procaccia		code	-1
Finding Friend and Foe in Multi-Agent Games	Jack Serrino, Max KleimanWeiner, David C. Parkes, Josh Tenenbaum		code	-1
Image Synthesis with a Single (Robust) Classifier	Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry		code	-1
Model Compression with Adversarial Robustness: A Unified Optimization Framework	Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu		code	-1
Cross-channel Communication Networks	Jianwei Yang, Zhile Ren, Chuang Gan, Hongyuan Zhu, Devi Parikh		code	-1
CondConv: Conditionally Parameterized Convolutions for Efficient Inference	Brandon Yang, Gabriel Bender, Quoc V. Le, Jiquan Ngiam		code	-1
Regression Planning Networks	Danfei Xu, Roberto MartínMartín, DeAn Huang, Yuke Zhu, Silvio Savarese, Li FeiFei		code	-1
Twin Auxilary Classifiers GAN	Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich		code	-1
Conditional Structure Generation through Graph Variational Generative Adversarial Nets	Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li		code	-1
Distributional Policy Optimization: An Alternative Approach for Continuous Control	Chen Tessler, Guy Tennenholtz, Shie Mannor		code	-1
Sampling Sketches for Concave Sublinear Functions of Frequencies	Edith Cohen, Ofir Geri		code	-1
Deliberative Explanations: visualizing network insecurities	Pei Wang, Nuno Vasconcelos		code	-1
Computing Full Conformal Prediction Set with Approximate Homotopy	Eugène Ndiaye, Ichiro Takeuchi		code	-1
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift	Stephan Rabanser, Stephan Günnemann, Zachary C. Lipton		code	-1
Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards	Siyuan Li, Rui Wang, Minxue Tang, Chongjie Zhang		code	-1
Multi-View Reinforcement Learning	Minne Li, Lisheng Wu, Jun Wang, Haitham BouAmmar		code	-1
Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution	Thang Vu, Hyunjun Jang, Trung X. Pham, Chang Dong Yoo		code	-1
Neural Diffusion Distance for Image Segmentation	Jian Sun, Zongben Xu		code	-1
Fine-grained Optimization of Deep Neural Networks	Mete Ozay		code	-1
Extending Stein's unbiased risk estimator to train deep denoisers with correlated pairs of noisy images	Magauiya Zhussip, Shakarim Soltanayev, Se Young Chun		code	-1
Fixing Implicit Derivatives: Trust-Region Based Learning of Continuous Energy Functions	Chris Russell, Matteo Toso, Neill D. F. Campbell		code	-1
Hyperspherical Prototype Networks	Pascal Mettes, Elise van der Pol, Cees Snoek		code	-1
Expressive power of tensor-network factorizations for probabilistic modeling	Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, J. Ignacio Cirac		code	-1
HyperGCN: A New Method For Training Graph Convolutional Networks on Hypergraphs	Naganand Yadati, Madhav Nimishakavi, Prateek Yadav, Vikram Nitin, Anand Louis, Partha P. Talukdar		code	-1
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points	Zhize Li		code	-1
Efficient Meta Learning via Minibatch Proximal Update	Pan Zhou, Xiaotong Yuan, Huan Xu, Shuicheng Yan, Jiashi Feng		code	-1
Unconstrained Monotonic Neural Networks	Antoine Wehenkel, Gilles Louppe		code	-1
Guided Similarity Separation for Image Retrieval	Chundi Liu, Guang Wei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti		code	-1
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss	Kaidi Cao, Colin Wei, Adrien Gaidon, Nikos Aréchiga, Tengyu Ma		code	-1
Strategizing against No-regret Learners	Yuan Deng, Jon Schneider, Balasubramanian Sivan		code	-1
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs	Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen		code	-1
Hierarchical Optimal Transport for Document Representation	Mikhail Yurochkin, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon		code	-1
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes	Rui Li		code	-1
Positional Normalization	Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie		code	-1
A New Defense Against Adversarial Images: Turning a Weakness into a Strength	Shengyuan Hu, Tao Yu, Chuan Guo, WeiLun Chao, Kilian Q. Weinberger		code	-1
Quadratic Video Interpolation	Xiangyu Xu, Li SiYao, Wenxiu Sun, Qian Yin, MingHsuan Yang		code	-1
ResNets Ensemble via the Feynman-Kac Formalism to Improve Natural and Robust Accuracies	Bao Wang, Zuoqiang Shi, Stanley J. Osher		code	-1
Incremental Scene Synthesis	Benjamin Planche, Xuejian Rong, Ziyan Wu, Srikrishna Karanam, Harald Kosch, Yingli Tian, Jan Ernst, Andreas Hutter		code	-1
Self-Supervised Generalisation with Meta Auxiliary Learning	Shikun Liu, Andrew J. Davison, Edward Johns		code	-1
Variational Denoising Network: Toward Blind Noise Modeling and Removal	Zongsheng Yue, Hongwei Yong, Qian Zhao, Deyu Meng, Lei Zhang		code	-1
Fast Sparse Group Lasso	Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima		code	-1
Learnable Tree Filter for Structure-preserving Feature Transform	Lin Song, Yanwei Li, Zeming Li, Gang Yu, Hongbin Sun, Jian Sun, Nanning Zheng		code	-1
Data-Dependence of Plateau Phenomenon in Learning with Neural Network - Statistical Mechanical Analysis	Yuki Yoshida, Masato Okada		code	-1
Coordinated hippocampal-entorhinal replay as structural inference	Talfan Evans, Neil Burgess		code	-1
Cascaded Dilated Dense Network with Two-step Data Consistency for MRI Reconstruction	Hao Zheng, Faming Fang, Guixu Zhang		code	-1
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning	Aaron Defazio, Léon Bottou		code	-1
On the Curved Geometry of Accelerated Optimization	Aaron Defazio		code	-1
Multi-marginal Wasserstein GAN	Jiezhang Cao, Langyuan Mo, Yifan Zhang, Kui Jia, Chunhua Shen, Mingkui Tan		code	-1
Better Exploration with Optimistic Actor Critic	Kamil Ciosek, Quan Vuong, Robert Loftin, Katja Hofmann		code	-1
Importance Resampling for Off-policy Prediction	Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White		code	-1
The Label Complexity of Active Learning from Observational Data	Songbai Yan, Kamalika Chaudhuri, Tara Javidi		code	-1
Meta-Learning Representations for Continual Learning	Khurram Javed, Martha White		code	-1
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training	Haichao Zhang, Jianyu Wang		code	-1
Visualizing the PHATE of Neural Networks	Scott Gigante, Adam S. Charles, Smita Krishnaswamy, Gal Mishne		code	-1
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers	Alex X. Lu, Amy X. Lu, Wiebke Schormann, Marzyeh Ghassemi, David W. Andrews, Alan M. Moses		code	-1
Nonconvex Low-Rank Tensor Completion from Noisy Data	Changxiao Cai, Gen Li, H. Vincent Poor, Yuxin Chen		code	-1
Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization	Gautam Goel, Yiheng Lin, Haoyuan Sun, Adam Wierman		code	-1
Channel Gating Neural Networks	Weizhe Hua, Yuan Zhou, Christopher De Sa, Zhiru Zhang, G. Edward Suh		code	-1
Neural networks grown and self-organized by noise	Guruprasad Raghavan, Matt Thomson		code	-1
Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning	Xinyang Chen, Sinan Wang, Bo Fu, Mingsheng Long, Jianmin Wang		code	-1
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting	Jun Shu, Qi Xie, Lixuan Yi, Qian Zhao, Sanping Zhou, Zongben Xu, Deyu Meng		code	-1
Variational Structured Semantic Inference for Diverse Image Captioning	Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang		code	-1
Mapping State Space using Landmarks for Universal Goal Reaching	Zhiao Huang, Fangchen Liu, Hao Su		code	-1
Transferable Normalization: Towards Improving Transferability of Deep Neural Networks	Ximei Wang, Ying Jin, Mingsheng Long, Jianmin Wang, Michael I. Jordan		code	-1
Random deep neural networks are biased towards simple functions	Giacomo De Palma, Bobak Toussi Kiani, Seth Lloyd		code	-1
XNAS: Neural Architecture Search with Expert Advice	Niv Nayman, Asaf Noy, Tal Ridnik, Itamar Friedman, Rong Jin, Lihi ZelnikManor		code	-1
CNN2: Viewpoint Generalization via a Binocular Vision	WeiDa Chen, ShanHung Wu		code	-1
Generalized Off-Policy Actor-Critic	Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson		code	-1
DAC: The Double Actor-Critic Architecture for Learning Options	Shangtong Zhang, Shimon Whiteson		code	-1
Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models	Tao Yu, Christopher De Sa		code	-1
Controlling Neural Level Sets	Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman		code	-1
Blended Matching Pursuit	Cyrille W. Combettes, Sebastian Pokutta		code	-1
An Improved Analysis of Training Over-parameterized Deep Neural Networks	Difan Zou, Quanquan Gu		code	-1
Controllable Text-to-Image Generation	Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr		code	-1
Improving Textual Network Learning with Variational Homophilic Embeddings	Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin		code	-1
Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach	Peilin Zhong, Yuchen Mo, Chang Xiao, Pengyu Chen, Changxi Zheng		code	-1
The Randomized Midpoint Method for Log-Concave Sampling	Ruoqi Shen, Yin Tat Lee		code	-1
Sample-Efficient Deep Reinforcement Learning via Episodic Backward Update	Su Young Lee, SungIk Choi, SaeYoung Chung		code	-1
Fully Neural Network based Model for General Temporal Point Processes	Takahiro Omi, Naonori Ueda, Kazuyuki Aihara		code	-1
Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks	Zhonghui You, Kun Yan, Jinmian Ye, Meng Ma, Ping Wang		code	-1
Discrimination in Online Markets: Effects of Social Bias on Learning from Reviews and Policy Design	Faidra Georgia Monachou, Itai Ashlagi		code	-1
Provably Powerful Graph Networks	Haggai Maron, Heli BenHamu, Hadar Serviansky, Yaron Lipman		code	-1
Order Optimal One-Shot Distributed Learning	Arsalan SharifNassab, Saber Salehkaleybar, S. Jamaloddin Golestani		code	-1
Information Competing Process for Learning Diversified Representations	Jie Hu, Rongrong Ji, Shengchuan Zhang, Xiaoshuai Sun, Qixiang Ye, ChiaWen Lin, Qi Tian		code	-1
GENO - GENeric Optimization for Classical Machine Learning	Sören Laue, Matthias Mitterreiter, Joachim Giesen		code	-1
Conditional Independence Testing using Generative Adversarial Networks	Alexis Bellot, Mihaela van der Schaar		code	-1
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function	Aviv Rosenberg, Yishay Mansour		code	-1
Partitioning Structure Learning for Segmented Linear Regression Trees	Xiangyu Zheng, Song Xi Chen		code	-1
A Tensorized Transformer for Language Modeling	Xindian Ma, Peng Zhang, Shuai Zhang, Nan Duan, Yuexian Hou, Ming Zhou, Dawei Song		code	-1
Kernel Stein Tests for Multiple Model Comparison	Jen Ning Lim, Makoto Yamada, Bernhard Schölkopf, Wittawat Jitkrittum		code	-1
Disentangled behavioural representations	Amir Dezfouli, Hassan Ashtiani, Omar Ghattas, Richard Nock, Peter Dayan, Cheng Soon Ong		code	-1
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation	Quanfu Fan, ChunFu (Richard) Chen, Hilde Kuehne, Marco Pistoia, David D. Cox		code	-1
Rethinking the CSC Model for Natural Images	Dror Simon, Michael Elad		code	-1
Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning	Weishi Shi, Qi Yu		code	-1
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity	Deepak Pathak, Christopher Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros		code	-1
Perceiving the arrow of time in autoregressive motion	Kristof Meding, Dominik Janzing, Bernhard Schölkopf, Felix A. Wichmann		code	-1
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections	Ofir Nachum, Yinlam Chow, Bo Dai, Lihong Li		code	-1
Hyper-Graph-Network Decoders for Block Codes	Eliya Nachmani, Lior Wolf		code	-1
Large Scale Markov Decision Processes with Changing Rewards	Adrian Rivera Cardoso, He Wang, Huan Xu		code	-1
Multiview Aggregation for Learning Category-Specific Shape Reconstruction	Srinath Sridhar, Davis Rempe, Julien Valentin, Sofien Bouaziz, Leonidas J. Guibas		code	-1
Semi-Parametric Dynamic Contextual Pricing	Virag Shah, Ramesh Johari, Jose H. Blanchet		code	-1
Interlaced Greedy Algorithm for Maximization of Submodular Functions in Nearly Linear Time	Alan Kuhnle		code	-1
Initialization of ReLUs for Dynamical Isometry	Rebekka Burkholz, Alina Dubatovka		code	-1
Gradient Information for Representation and Modeling	Jie Ding, A. Robert Calderbank, Vahid Tarokh		code	-1
SpiderBoost and Momentum: Faster Variance Reduction Algorithms	Zhe Wang, Kaiyi Ji, Yi Zhou, Yingbin Liang, Vahid Tarokh		code	-1
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases	Xiyang Liu, Sewoong Oh		code	-1
Backprop with Approximate Activations for Memory-efficient Network Training	Ayan Chakrabarti, Benjamin Moseley		code	-1
Training Image Estimators without Image Ground Truth	Zhihao Xia, Ayan Chakrabarti		code	-1
Deep Structured Prediction for Facial Landmark Detection	Lisha Chen, Hui Su, Qiang Ji		code	-1
Information-Theoretic Confidence Bounds for Reinforcement Learning	Xiuyuan Lu, Benjamin Van Roy		code	-1
Transfer Anomaly Detection by Inferring Latent Domain Representations	Atsutoshi Kumagai, Tomoharu Iwata, Yasuhiro Fujiwara		code	-1
Total Least Squares Regression in Input Sparsity Time	Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang		code	-1
Park: An Open Platform for Learning-Augmented Computer Systems	Hongzi Mao, Parimarjan Negi, Akshay Narayan, Hanrui Wang, Jiacheng Yang, Haonan Wang, Ryan Marcus, Ravichandra Addanki, Mehrdad Khani Shirkoohi, Songtao He, Vikram Nathan, Frank Cangialosi, Shaileshh Bojja Venkatakrishnan, WeiHung Weng, Song Han, Tim Kraska, Mohammad Alizadeh		code	-1
Adapting Neural Networks for the Estimation of Treatment Effects	Claudia Shi, David M. Blei, Victor Veitch		code	-1
Learning Transferable Graph Exploration	Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, PoSen Huang, Pushmeet Kohli		code	-1
Conformal Prediction Under Covariate Shift	Ryan J. Tibshirani, Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas		code	-1
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation	Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar		code	-1
Asymmetric Valleys: Beyond Sharp and Flat Local Minima	Haowei He, Gao Huang, Yang Yuan		code	-1
Positive-Unlabeled Compression on the Cloud	Yixing Xu, Yunhe Wang, Hanting Chen, Kai Han, Chunjing Xu, Dacheng Tao, Chang Xu		code	-1
Direct Estimation of Differential Functional Graphical Models	Boxin Zhao, Y. Samuel Wang, Mladen Kolar		code	-1
On the Calibration of Multiclass Classification with Rejection	Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama		code	-1
Third-Person Visual Imitation Learning via Decoupled Hierarchical Controller	Pratyusha Sharma, Deepak Pathak, Abhinav Gupta		code	-1
Stagewise Training Accelerates Convergence of Testing Error Over SGD	Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang		code	-1
Learning Robust Options by Conditional Value at Risk Optimization	Takuya Hiraoka, Takahisa Imagawa, Tatsuya Mori, Takashi Onishi, Yoshimasa Tsuruoka		code	-1
Non-asymptotic Analysis of Stochastic Methods for Non-Smooth Non-Convex Regularized Problems	Yi Xu, Rong Jin, Tianbao Yang		code	-1
On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective	Lili Su, Pengkun Yang		code	-1
Drill-down: Interactive Retrieval of Complex Scenes using Natural Language Queries	Fuwen Tan, Paola CascanteBonilla, Xiaoxiao Guo, Hui Wu, Song Feng, Vicente Ordonez		code	-1
Dual Variational Generation for Low Shot Heterogeneous Face Recognition	Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He		code	-1
Discovering Neural Wirings	Mitchell Wortsman, Ali Farhadi, Mohammad Rastegari		code	-1
On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems	Baekjin Kim, Ambuj Tewari		code	-1
Knowledge Extraction with No Observable Data	Jaemin Yoo, Minyong Cho, Taebum Kim, U Kang		code	-1
PAC-Bayes under potentially heavy tails	Matthew J. Holland		code	-1
One-Shot Object Detection with Co-Attention and Co-Excitation	TingI Hsieh, YiChen Lo, HwannTzong Chen, TyngLuh Liu		code	-1
Quaternion Knowledge Graph Embeddings	Shuai Zhang, Yi Tay, Lina Yao, Qi Liu		code	-1
Glyce: Glyph-vectors for Chinese Character Representations	Yuxian Meng, Wei Wu, Fei Wang, Xiaoya Li, Ping Nie, Fan Yin, Muyu Li, Qinghong Han, Xiaofei Sun, Jiwei Li		code	-1
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels	Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath		code	-1
Heterogeneous Graph Learning for Visual Commonsense Reasoning	Weijiang Yu, Jingwen Zhou, Weihao Yu, Xiaodan Liang, Nong Xiao		code	-1
Probabilistic Watershed: Sampling all spanning forests for seeded segmentation and semi-supervised learning	Enrique Fita Sanmartin, Sebastian Damrich, Fred A. Hamprecht		code	-1
Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components	Sascha Saralajew, Lars Holdijk, Maike Rees, Ebubekir Asan, Thomas Villmann		code	-1
Identifying Causal Effects via Context-specific Independence Relations	Santtu Tikka, Antti Hyttinen, Juha Karvanen		code	-1
Bridging Machine Learning and Logical Reasoning by Abductive Learning	WangZhou Dai, QiuLing Xu, Yang Yu, ZhiHua Zhou		code	-1
Regret Minimization for Reinforcement Learning by Evaluating the Optimal Bias Function	Zihan Zhang, Xiangyang Ji		code	-1
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods	Belhal Karimi, HoiTo Wai, Eric Moulines, Marc Lavielle		code	-1
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization	Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed		code	-1
Regularizing Trajectory Optimization with Denoising Autoencoders	Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola		code	-1
Learning Hierarchical Priors in VAEs	Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt		code	-1
Epsilon-Best-Arm Identification in Pay-Per-Reward Multi-Armed Bandits	Sivan Sabato		code	-1
Safe Exploration for Interactive Machine Learning	Matteo Turchetta, Felix Berkenkamp, Andreas Krause		code	-1
Addressing Failure Prediction by Learning Model Confidence	Charles Corbière, Nicolas Thome, Avner BarHen, Matthieu Cord, Patrick Pérez		code	-1
Combinatorial Bayesian Optimization using the Graph Cartesian Product	ChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling		code	-1
Fooling Neural Network Interpretations via Adversarial Model Manipulation	Juyeon Heo, Sunghwan Joo, Taesup Moon		code	-1
On Lazy Training in Differentiable Programming	Lénaïc Chizat, Edouard Oyallon, Francis R. Bach		code	-1
Quality Aware Generative Adversarial Networks	Parimala Kancharla, Sumohana S. Channappayya		code	-1
Copula-like Variational Inference	Marcel Hirt, Petros Dellaportas, Alain Durmus		code	-1
Implicit Regularization for Optimal Sparse Recovery	Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini		code	-1
Locally Private Gaussian Estimation	Matthew Joseph, Janardhan Kulkarni, Jieming Mao, Zhiwei Steven Wu		code	-1
Multi-mapping Image-to-Image Translation via Learning Disentanglement	Xiaoming Yu, Yuanqi Chen, Shan Liu, Thomas H. Li, Ge Li		code	-1
Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs	Yusuke Tanaka, Toshiyuki Tanaka, Tomoharu Iwata, Takeshi Kurashima, Maya Okawa, Yasunori Akagi, Hiroyuki Toda		code	-1
Fast Structured Decoding for Sequence Models	Zhiqing Sun, Zhuohan Li, Haoqing Wang, Di He, Zi Lin, ZhiHong Deng		code	-1
Learning Temporal Pose Estimation from Sparsely-Labeled Videos	Gedas Bertasius, Christoph Feichtenhofer, Du Tran, Jianbo Shi, Lorenzo Torresani		code	-1
Putting An End to End-to-End: Gradient-Isolated Learning of Representations	Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling		code	-1
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching	Hongteng Xu, Dixin Luo, Lawrence Carin		code	-1
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition	Satoshi Tsutsui, Yanwei Fu, David J. Crandall		code	-1
Real-Time Reinforcement Learning	Simon Ramstedt, Chris Pal		code	-1
Robust Multi-agent Counterfactual Prediction	Alexander Peysakhovich, Christian Kroer, Adam Lerer		code	-1
Approximate Inference Turns Deep Networks into Gaussian Processes	Mohammad Emtiyaz Khan, Alexander Immer, Ehsan Abedi, Maciej Korzepa		code	-1
Deep Signature Transforms	Patrick Kidger, Patric Bonnier, Imanol Pérez Arribas, Cristopher Salvi, Terry J. Lyons		code	-1
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits	Yogev BarOn, Yishay Mansour		code	-1
Convergent Policy Optimization for Safe Reinforcement Learning	Ming Yu, Zhuoran Yang, Mladen Kolar, Zhaoran Wang		code	-1
Augmented Neural ODEs	Emilien Dupont, Arnaud Doucet, Yee Whye Teh		code	-1
Thompson Sampling for Multinomial Logit Contextual Bandits	Minhwan Oh, Garud Iyengar		code	-1
Backpropagation-Friendly Eigendecomposition	Wei Wang, Zheng Dang, Yinlin Hu, Pascal Fua, Mathieu Salzmann		code	-1
FastSpeech: Fast, Robust and Controllable Text to Speech	Yi Ren, Yangjun Ruan, Xu Tan, Tao Qin, Sheng Zhao, Zhou Zhao, TieYan Liu		code	-1
Ultrametric Fitting by Gradient Descent	Giovanni Chierchia, Benjamin Perret		code	-1
Distinguishing Distributions When Samples Are Strategically Transformed	Hanrui Zhang, Yu Cheng, Vincent Conitzer		code	-1
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks	Gauthier Gidel, Francis R. Bach, Simon LacosteJulien		code	-1
Deep Set Prediction Networks	Yan Zhang, Jonathon S. Hare, Adam PrügelBennett		code	-1
DppNet: Approximating Determinantal Point Processes with Deep Networks	Zelda E. Mariet, Yaniv Ovadia, Jasper Snoek		code	-1
Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control	Sai Qian Zhang, Qi Zhang, Jieyu Lin		code	-1
Neural Lyapunov Control	YaChien Chang, Nima Roohi, Sicun Gao		code	-1
Fully Dynamic Consistent Facility Location	Vincent CohenAddad, Niklas Hjuler, Nikos Parotsidis, David Saulpic, Chris Schwiegelshohn		code	-1
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems	Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, Samuel R. Bowman		code	-1
A Flexible Generative Framework for Graph-based Semi-supervised Learning	Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei		code	-1
Inherent Weight Normalization in Stochastic Neural Networks	Georgios Detorakis, Sourav Dutta, Abhishek Khanna, Matthew Jerry, Suman Datta, Emre Neftci		code	-1
Optimal Decision Tree with Noisy Outcomes	Su Jia, Viswanath Nagarajan, Fatemeh Navidi, R. Ravi		code	-1
Meta-Curvature	Eunbyung Park, Junier B. Oliva		code	-1
Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning	Nathan Kallus, Masatoshi Uehara		code	-1
KerGM: Kernelized Graph Matching	Zhen Zhang, Yijian Xiang, Lingfei Wu, Bing Xue, Arye Nehorai		code	-1
Transfusion: Understanding Transfer Learning for Medical Imaging	Maithra Raghu, Chiyuan Zhang, Jon M. Kleinberg, Samy Bengio		code	-1
Adversarial training for free!	Ali Shafahi, Mahyar Najibi, Amin Ghiasi, Zheng Xu, John P. Dickerson, Christoph Studer, Larry S. Davis, Gavin Taylor, Tom Goldstein		code	-1
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients	Jun Sun, Tianyi Chen, Georgios B. Giannakis, Zaiyue Yang		code	-1
Implicitly learning to reason in first-order logic	Vaishak Belle, Brendan Juba		code	-1
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods	Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin		code	-1
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness	Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong		code	-1
Arbicon-Net: Arbitrary Continuous Geometric Transformation Networks for Image Registration	Jianchun Chen, Lingjing Wang, Xiang Li, Yi Fang		code	-1
Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds	Nathan Kallus, Angela Zhou		code	-1
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric	Nathan Kallus, Angela Zhou		code	-1
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models	Sharon Zhou, Mitchell L. Gordon, Ranjay Krishna, Austin Narcomey, Li FeiFei, Michael S. Bernstein		code	-1
First order expansion of convex regularized estimators	Pierre C. Bellec, Arun K. Kuchibhotla		code	-1
Capacity Bounded Differential Privacy	Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala		code	-1
Universal Boosting Variational Inference	Trevor Campbell, Xinglong Li		code	-1
SGD on Neural Networks Learns Functions of Increasing Complexity	Dimitris Kalimeris, Gal Kaplun, Preetum Nakkiran, Benjamin L. Edelman, Tristan Yang, Boaz Barak, Haofeng Zhang		code	-1
The Landscape of Non-convex Empirical Risk with Degenerate Population Risk	Shuang Li, Gongguo Tang, Michael B. Wakin		code	-1
Making AI Forget You: Data Deletion in Machine Learning	Antonio Ginart, Melody Y. Guan, Gregory Valiant, James Zou		code	-1
Practical Differentially Private Top-k Selection with Pay-what-you-get Composition	David Durfee, Ryan M. Rogers		code	-1
Conformalized Quantile Regression	Yaniv Romano, Evan Patterson, Emmanuel J. Candès		code	-1
Thompson Sampling with Information Relaxation Penalties	Seungki Min, Costis Maglaras, Ciamac C. Moallemi		code	-1
Deep Generalized Method of Moments for Instrumental Variable Analysis	Andrew Bennett, Nathan Kallus, Tobias Schnabel		code	-1
Learning Sample-Specific Models with Low-Rank Personalized Regression	Benjamin J. Lengerich, Bryon Aragam, Eric P. Xing		code	-1
Dancing to Music	HsinYing Lee, Xiaodong Yang, MingYu Liu, TingChun Wang, YuDing Lu, MingHsuan Yang, Jan Kautz		code	-1
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask	Hattie Zhou, Janice Lan, Rosanne Liu, Jason Yosinski		code	-1
Implicit Generation and Modeling with Energy Based Models	Yilun Du, Igor Mordatch		code	-1
LCA: Loss Change Allocation for Neural Network Training	Janice Lan, Rosanne Liu, Hattie Zhou, Jason Yosinski		code	-1
Predicting the Politics of an Image Using Webly Supervised Data	Christopher Thomas, Adriana Kovashka		code	-1
Adaptive GNN for Image Analysis and Editing	Lingyu Liang, Lianwen Jin, Yong Xu		code	-1
Ultra Fast Medoid Identification via Correlated Sequential Halving	Tavor Z. Baharav, David Tse		code	-1
Tight Dimension Independent Lower Bound on the Expected Convergence Rate for Diminishing Step Sizes in SGD	Phuong Ha Nguyen, Lam M. Nguyen, Marten van Dijk		code	-1
Asymptotics for Sketching in Least Squares Regression	Edgar Dobriban, Sifan Liu		code	-1
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies	Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine		code	-1
Exact inference in structured prediction	Kevin Bello, Jean Honorio		code	-1
Coda: An End-to-End Neural Program Decompiler	Cheng Fu, Huili Chen, Haolan Liu, Xinyun Chen, Yuandong Tian, Farinaz Koushanfar, Jishen Zhao		code	-1
Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes	Gunpil Hwang, Seohyeon Kim, HyeonMin Bae		code	-1
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates	Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon LacosteJulien		code	-1
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data	Dominik Linzner, Michael Schmidt, Heinz Koeppl		code	-1
Privacy-Preserving Classification of Personal Text Messages with Secure Multi-Party Computation	Devin Reich, Ariel Todoki, Rafael Dowsley, Martine De Cock, Anderson C. A. Nascimento		code	-1
Efficiently Estimating Erdos-Renyi Graphs with Node Differential Privacy	Jonathan R. Ullman, Adam Sealfon		code	-1
Learning Representations for Time Series Clustering	Qianli Ma, Jiawei Zheng, Sen Li, Gary W. Cottrell		code	-1
Verified Uncertainty Calibration	Ananya Kumar, Percy Liang, Tengyu Ma		code	-1
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits	Wenhao Zhang, Si Wu, Brent Doiron, Tai Sing Lee		code	-1
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction	Yunji Kim, Seonghyeon Nam, In Cho, Seon Joo Kim		code	-1
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks	Yiwen Guo, Ziang Yan, Changshui Zhang		code	-1
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction	Difan Zou, Pan Xu, Quanquan Gu		code	-1
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling	Qitian Wu, Zixuan Zhang, Xiaofeng Gao, Junchi Yan, Guihai Chen		code	-1
Cross-sectional Learning of Extremal Dependence among Financial Assets	Xing Yan, Qi Wu, Wen Zhang		code	-1
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG	Yujia Jin, Aaron Sidford		code	-1
Compression with Flows via Local Bits-Back Coding	Jonathan Ho, Evan Lohn, Pieter Abbeel		code	-1
Exact Rate-Distortion in Autoencoders via Echo Noise	Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg		code	-1
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI	Qianqian Xu, Xinwei Sun, Zhiyong Yang, Xiaochun Cao, Qingming Huang, Yuan Yao		code	-1
Domes to Drones: Self-Supervised Active Triangulation for 3D Human Pose Reconstruction	Aleksis Pirinen, Erik Gärtner, Cristian Sminchisescu		code	-1
MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization	Shangyu Chen, Wenya Wang, Sinno Jialin Pan		code	-1
Improved Precision and Recall Metric for Assessing Generative Models	Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, Timo Aila		code	-1
A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression	Jiajin Li, Sen Huang, Anthony ManCho So		code	-1
PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph	Yikang Li, Tao Ma, Yeqi Bai, Nan Duan, Sining Wei, Xiaogang Wang		code	-1
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso	Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon		code	-1
Joint Optimization of Tree-based Index and Deep Model for Recommender Systems	Han Zhu, Daqing Chang, Ziru Xu, Pengye Zhang, Xiang Li, Jie He, Han Li, Jian Xu, Kun Gai		code	-1
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning	Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta, Hongzi Mao, Mohammad Alizadeh		code	-1
Uncoupled Regression from Pairwise Comparison Data	Liyuan Xu, Junya Honda, Gang Niu, Masashi Sugiyama		code	-1
Cross Attention Network for Few-shot Classification	Ruibing Hou, Hong Chang, Bingpeng Ma, Shiguang Shan, Xilin Chen		code	-1
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution	Qing Qu, Xiao Li, Zhihui Zhu		code	-1
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models	Linfeng Zhang, Zhanhong Tan, Jiebo Song, Jingwei Chen, Chenglong Bao, Kaisheng Ma		code	-1
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs	Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay		code	-1
Teaching Multiple Concepts to a Forgetful Learner	Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla		code	-1
Regularized Weighted Low Rank Approximation	Frank Ban, David P. Woodruff, Qiuyi (Richard) Zhang		code	-1
Practical and Consistent Estimation of f-Divergences	Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin		code	-1
Approximation Ratios of Graph Neural Networks for Combinatorial Problems	Ryoma Sato, Makoto Yamada, Hisashi Kashima		code	-1
Thinning for Accelerating the Learning of Point Processes	Tianbo Li, Yiping Ke		code	-1
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models	Maksim Kuznetsov, Daniil Polykovskiy, Dmitry P. Vetrov, Alexander Zhebrak		code	-1
Differentially Private Markov Chain Monte Carlo	Mikko A. Heikkilä, Joonas Jälkö, Onur Dikmen, Antti Honkela		code	-1
Full-Gradient Representation for Neural Network Visualization	Suraj Srinivas, François Fleuret		code	-1
q-means: A quantum algorithm for unsupervised machine learning	Iordanis Kerenidis, Jonas Landman, Alessandro Luongo, Anupam Prakash		code	-1
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints	Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla		code	-1
Limitations of the empirical Fisher approximation for natural gradient descent	Frederik Kunstner, Philipp Hennig, Lukas Balles		code	-1
Flow-based Image-to-Image Translation with Feature Disentanglement	Ruho Kondo, Keisuke Kawano, Satoshi Koide, Takuro Kutsuna		code	-1
Learning dynamic polynomial proofs	Alhussein Fawzi, Mateusz Malinowski, Hamza Fawzi, Omar Fawzi		code	-1
Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models	Vincent Le Guen, Nicolas Thome		code	-1
Understanding Attention and Generalization in Graph Neural Networks	Boris Knyazev, Graham W. Taylor, Mohamed R. Amer		code	-1
Data Cleansing for Models Trained with SGD	Satoshi Hara, Atsushi Nitanda, Takanori Maehara		code	-1
Curvilinear Distance Metric Learning	Shuo Chen, Lei Luo, Jian Yang, Chen Gong, Jun Li, Heng Huang		code	-1
Embedding Symbolic Knowledge into Deep Networks	Yaqi Xie, Ziwei Xu, Kuldeep S. Meel, Mohan S. Kankanhalli, Harold Soh		code	-1
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections	Raanan Y. Yehezkel Rohekar, Yaniv Gurwicz, Shami Nisimov, Gal Novik		code	-1
Efficient Graph Generation with Graph Recurrent Attention Networks	Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel		code	-1
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms	Mahesh Chandra Mukkamala, Peter Ochs		code	-1
Learning Deep Bilinear Transformation for Fine-grained Image Representation	Heliang Zheng, Jianlong Fu, ZhengJun Zha, Jiebo Luo		code	-1
Practical Deep Learning with Bayesian Principles	Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota		code	-1
Training Language GANs from Scratch	Cyprien de Masson d'Autume, Shakir Mohamed, Mihaela Rosca, Jack W. Rae		code	-1
Pseudo-Extended Markov chain Monte Carlo	Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman		code	-1
Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate	James Jordon, Jinsung Yoon, Mihaela van der Schaar		code	-1
Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters	Alberto Maria Metelli, Amarildo Likmeta, Marcello Restelli		code	-1
On Adversarial Mixup Resynthesis	Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal		code	-1
A Geometric Perspective on Optimal Representations for Reinforcement Learning	Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle		code	-1
Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks	Joshua K. Lee, Prasanna Sattigeri, Gregory W. Wornell		code	-1
Understanding and Improving Layer Normalization	Jingjing Xu, Xu Sun, Zhiyuan Zhang, Guangxiang Zhao, Junyang Lin		code	-1
Uncertainty-based Continual Learning with Adaptive Regularization	Hongjoon Ahn, Sungmin Cha, Donggyu Lee, Taesup Moon		code	-1
LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning	Yali Du, Lei Han, Meng Fang, Ji Liu, Tianhong Dai, Dacheng Tao		code	-1
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging	Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jørgen Jennum, Christian Igel		code	-1
Massively scalable Sinkhorn distances via the Nyström method	Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan NilesWeed		code	-1
Double Quantization for Communication-Efficient Distributed Optimization	Yue Yu, Jiaxiang Wu, Longbo Huang		code	-1
Globally optimal score-based learning of directed acyclic graphs in high-dimensions	Bryon Aragam, Arash A. Amini, Qing Zhou		code	-1
Multi-relational Poincaré Graph Embeddings	Ivana Balazevic, Carl Allen, Timothy M. Hospedales		code	-1
No-Press Diplomacy: Modeling Multi-Agent Gameplay	Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya OrtizGagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville		code	-1
State Aggregation Learning from Markov Transition Data	Yaqi Duan, Zheng Tracy Ke, Mengdi Wang		code	-1
Disentangling Influence: Using disentangled representations to audit model predictions	Charles T. Marx, Richard L. Phillips, Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian		code	-1
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning	David Janz, Jiri Hron, Przemyslaw Mazur, Katja Hofmann, José Miguel HernándezLobato, Sebastian Tschiatschek		code	-1
Partially Encrypted Deep Learning using Functional Encryption	Théo Ryffel, David Pointcheval, Francis R. Bach, Edouard DufourSans, Romain Gay		code	-1
Decentralized Cooperative Stochastic Bandits	David MartínezRubio, Varun Kanade, Patrick Rebeschini		code	-1
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem	Gonzalo Mena, Jonathan NilesWeed		code	-1
Efficient Deep Approximation of GMMs	Shirin Jalali, Carl J. Nuzman, Iraj Saniee		code	-1
Learning low-dimensional state embeddings and metastable clusters from time series data	Yifan Sun, Yaqi Duan, Hao Gong, Mengdi Wang		code	-1
Exploiting Local and Global Structure for Point Cloud Semantic Segmentation with Contextual Point Representations	Xu Wang, Jingming He, Lin Ma		code	-1
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes	Creighton Heaukulani, Mark van der Wilk		code	-1
Kernel Instrumental Variable Regression	Rahul Singh, Maneesh Sahani, Arthur Gretton		code	-1
Symmetry-Based Disentangled Representation Learning requires Interaction with Environments	Hugo CasellesDupré, Michaël Garcia Ortiz, David Filliat		code	-1
Fast Efficient Hyperparameter Tuning for Policy Gradient Methods	Supratik Paul, Vitaly Kurin, Shimon Whiteson		code	-1
Offline Contextual Bayesian Optimization	Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen		code	-1
Making the Cut: A Bandit-based Approach to Tiered Interviewing	Candice Schumann, Zhi Lang, Jeffrey S. Foster, John P. Dickerson		code	-1
Unsupervised Scalable Representation Learning for Multivariate Time Series	JeanYves Franceschi, Aymeric Dieuleveut, Martin Jaggi		code	-1
A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI	Tao Tu, John W. Paisley, Stefan Haufe, Paul Sajda		code	-1
End to end learning and optimization on graphs	Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe		code	-1
Game Design for Eliciting Distinguishable Behavior	Fan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen		code	-1
When does label smoothing help?	Rafael Müller, Simon Kornblith, Geoffrey E. Hinton		code	-1
Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning	Harsh Gupta, R. Srikant, Lei Ying		code	-1
Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks	Lixin Fan, Kam Woh Ng, Chee Seng Chan		code	-1
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference	Cole L. Hurwitz, Kai Xu, Akash Srivastava, Alessio Paolo Buccino, Matthias H. Hennig		code	-1
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation	Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff		code	-1
Distribution-Independent PAC Learning of Halfspaces with Massart Noise	Ilias Diakonikolas, Themis Gouleakis, Christos Tzamos		code	-1
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies	Ronen Basri, David W. Jacobs, Yoni Kasten, Shira Kritchman		code	-1
Adaptive Auxiliary Task Weighting for Reinforcement Learning	Xingyu Lin, Harjatin Singh Baweja, George Kantor, David Held		code	-1
Blocking Bandits	Soumya Basu, Rajat Sen, Sujay Sanghavi, Sanjay Shakkottai		code	-1
Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities	Wei Qian, Yuqian Zhang, Yudong Chen		code	-1
Prior-Free Dynamic Auctions with Low Regret Buyers	Yuan Deng, Jon Schneider, Balasubramanian Sivan		code	-1
On Single Source Robustness in Deep Fusion Models	Taewan Kim, Joydeep Ghosh		code	-1
Policy Evaluation with Latent Confounders via Optimal Balance	Andrew Bennett, Nathan Kallus		code	-1
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting	Rajat Sen, HsiangFu Yu, Inderjit S. Dhillon		code	-1
Adaptive Cross-Modal Few-shot Learning	Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin, Pedro O. Pinheiro		code	-1
Spectral Modification of Graphs for Improved Spectral Clustering	Ioannis Koutis, Huong Le		code	-1
Hyperbolic Graph Convolutional Neural Networks	Ines Chami, Zhitao Ying, Christopher Ré, Jure Leskovec		code	-1
Cost Effective Active Search	Shali Jiang, Roman Garnett, Benjamin Moseley		code	-1
Exploration Bonus for Regret Minimization in Discrete and Continuous Average Reward MDPs	Jian Qian, Ronan Fruit, Matteo Pirotta, Alessandro Lazaric		code	-1
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks	Xiao Sun, Jungwook Choi, ChiaYu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan		code	-1
Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers	GuangHe Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola		code	-1
Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees	Ruqi Zhang, Christopher De Sa		code	-1
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers	Ari S. Morcos, Haonan Yu, Michela Paganini, Yuandong Tian		code	-1
Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces	Chuan Guo, Ali Mousavi, Xiang Wu, Daniel Niels HoltmannRice, Satyen Kale, Sashank J. Reddi, Sanjiv Kumar		code	-1
Fair Algorithms for Clustering	Suman Kalyan Bera, Deeparnab Chakrabarty, Nicolas Flores, Maryam Negahbani		code	-1
Learning Mean-Field Games	Xin Guo, Anran Hu, Renyuan Xu, Junzi Zhang		code	-1
SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers	Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough		code	-1
Deep imitation learning for molecular inverse problems	Eric Jonas		code	-1
Visual Concept-Metaconcept Learning	Chi Han, Jiayuan Mao, Chuang Gan, Josh Tenenbaum, Jiajun Wu		code	-1
Few-shot Video-to-Video Synthesis	TingChun Wang, MingYu Liu, Andrew Tao, Guilin Liu, Bryan Catanzaro, Jan Kautz		code	-1
Neural Similarity Learning	Weiyang Liu, Zhen Liu, James M. Rehg, Le Song		code	-1
Ordered Memory	Yikang Shen, Shawn Tan, Seyed Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron C. Courville		code	-1
MixMatch: A Holistic Approach to Semi-Supervised Learning	David Berthelot, Nicholas Carlini, Ian J. Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel		code	-1
Multivariate Triangular Quantile Maps for Novelty Detection	Jingjing Wang, Sun Sun, Yaoliang Yu		code	-1
Fast Parallel Algorithms for Statistical Subset Selection Problems	Sharon Qian, Yaron Singer		code	-1
PHYRE: A New Benchmark for Physical Reasoning	Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross B. Girshick		code	-1
On the number of variables to use in principal component regression	Ji Xu, Daniel J. Hsu		code	-1
Factor Group-Sparse Regularization for Efficient Low-Rank Matrix Recovery	Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell		code	-1
Mutually Regressive Point Processes	Ifigeneia Apostolopoulou, Scott W. Linderman, Kyle Miller, Artur Dubrawski		code	-1
Data-driven Estimation of Sinusoid Frequencies	Gautier Izacard, Sreyas Mohan, Carlos FernandezGranda		code	-1
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings	Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang		code	-1
ANODEV2: A Coupled Neural ODE Framework	Tianjun Zhang, Zhewei Yao, Amir Gholami, Joseph E. Gonzalez, Kurt Keutzer, Michael W. Mahoney, George Biros		code	-1
Estimating Entropy of Distributions in Constant Space	Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun		code	-1
On the Utility of Learning about Humans for Human-AI Coordination	Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan		code	-1
Efficient Regret Minimization Algorithm for Extensive-Form Correlated Equilibrium	Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm		code	-1
Learning in Generalized Linear Contextual Bandits with Stochastic Delays	Zhengyuan Zhou, Renyuan Xu, Jose H. Blanchet		code	-1
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness	Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody, David Evans		code	-1
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions	Gabriele Farina, Christian Kroer, Tuomas Sandholm		code	-1
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model	Erik Nijkamp, Mitch Hill, SongChun Zhu, Ying Nian Wu		code	-1
Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting	Shiyang Li, Xiaoyong Jin, Yao Xuan, Xiyou Zhou, Wenhu Chen, YuXiang Wang, Xifeng Yan		code	-1
On the Accuracy of Influence Functions for Measuring Group Effects	Pang Wei Koh, KaiSiang Ang, Hubert H. K. Teo, Percy Liang		code	-1
Face Reconstruction from Voice using Generative Adversarial Networks	Yandong Wen, Bhiksha Raj, Rita Singh		code	-1
Incremental Few-Shot Learning with Attention Attractor Networks	Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel		code	-1
On Testing for Biases in Peer Review	Ivan Stelmakh, Nihar B. Shah, Aarti Singh		code	-1
Learning Disentangled Representation for Robust Person Re-identification	Chanho Eom, Bumsub Ham		code	-1
Balancing Efficiency and Fairness in On-Demand Ridesourcing	Nixie S. Lesmana, Xuan Zhang, Xiaohui Bei		code	-1
Latent Ordinary Differential Equations for Irregularly-Sampled Time Series	Yulia Rubanova, Tian Qi Chen, David Duvenaud		code	-1
Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion	Yiqi Zhong, ChoYing Wu, Suya You, Ulrich Neumann		code	-1
Input Similarity from the Neural Network Perspective	Guillaume Charpiat, Nicolas Girard, Loris Felardos, Yuliya Tarabalka		code	-1
Adaptive Sequence Submodularity	Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi		code	-1
Weight Agnostic Neural Networks	Adam Gaier, David Ha		code	-1
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction	C. Daniel Freeman, David Ha, Luke Metz		code	-1
Reducing the variance in online optimization by transporting past gradients	Sébastien M. R. Arnold, PierreAntoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas, Nicolas Le Roux		code	-1
Characterizing Bias in Classifiers using Generative Models	Daniel McDuff, Shuang Ma, Yale Song, Ashish Kapoor		code	-1
Optimal Stochastic and Online Learning with Individual Iterates	Yunwen Lei, Peng Yang, Ke Tang, DingXuan Zhou		code	-1
Policy Learning for Fairness in Ranking	Ashudeep Singh, Thorsten Joachims		code	-1
Off-Policy Evaluation via Off-Policy Classification	Alexander Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine		code	-1
Regularized Gradient Boosting	Corinna Cortes, Mehryar Mohri, Dmitry Storcheus		code	-1
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model	Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley GramHansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood		code	-1
Markov Random Fields for Collaborative Filtering	Harald Steck		code	-1
A Step Toward Quantifying Independently Reproducible Machine Learning Research	Edward Raff		code	-1
Scalable Global Optimization via Local Bayesian Optimization	David Eriksson, Michael Pearce, Jacob R. Gardner, Ryan Turner, Matthias Poloczek		code	-1
Time-series Generative Adversarial Networks	Jinsung Yoon, Daniel Jarrett, Mihaela van der Schaar		code	-1
Ouroboros: On Accelerating Training of Transformer-Based Language Models	Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Lawrence Carin		code	-1
A Refined Margin Distribution Analysis for Forest Representation Learning	ShenHuan Lyu, Liang Yang, ZhiHua Zhou		code	-1
Robustness to Adversarial Perturbations in Learning from Incomplete Data	Amir Najafi, Shinichi Maeda, Masanori Koyama, Takeru Miyato		code	-1
Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks	Kohei Hayashi, Taiki Yamaguchi, Yohei Sugawara, Shinichi Maeda		code	-1
An Adaptive Empirical Bayesian Method for Sparse Deep Learning	Wei Deng, Xiao Zhang, Faming Liang, Guang Lin		code	-1
Adaptive Influence Maximization with Myopic Feedback	Binghui Peng, Wei Chen		code	-1
Focused Quantization for Sparse CNNs	Yiren Zhao, Xitong Gao, Daniel Bates, Robert D. Mullins, ChengZhong Xu		code	-1
Quantum Embedding of Knowledge for Reasoning	Dinesh Garg, Shajith Ikbal, Santosh K. Srivastava, Harit Vishwakarma, Hima P. Karanam, L. Venkata Subramaniam		code	-1
Optimal Best Markovian Arm Identification with Fixed Confidence	Vrettos Moulos		code	-1
Limiting Extrapolation in Linear Approximate Value Iteration	Andrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill		code	-1
Almost Horizon-Free Structure-Aware Best Policy Identification with a Generative Model	Andrea Zanette, Mykel J. Kochenderfer, Emma Brunskill		code	-1
Invertible Convolutional Flow	Mahdi Karami, Dale Schuurmans, Jascha SohlDickstein, Laurent Dinh, Daniel Duckworth		code	-1
A Latent Variational Framework for Stochastic Optimization	Philippe Casgrain		code	-1
Topology-Preserving Deep Image Segmentation	Xiaoling Hu, Fuxin Li, Dimitris Samaras, Chao Chen		code	-1
Connective Cognition Network for Directional Visual Commonsense Reasoning	Aming Wu, Linchao Zhu, Yahong Han, Yi Yang		code	-1
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms	Vikas K. Garg, Tamar Pichkhadze		code	-1
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning	Francisco M. Garcia, Philip S. Thomas		code	-1
Push-pull Feedback Implements Hierarchical Information Retrieval Efficiently	Xiao Liu, Xiaolong Zou, Zilong Ji, Gengshuo Tian, Yuanyuan Mi, Tiejun Huang, K. Y. Michael Wong, Si Wu		code	-1
Learning Disentangled Representations for Recommendation	Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang, Wenwu Zhu		code	-1
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels	Simon S. Du, Kangcheng Hou, Ruslan Salakhutdinov, Barnabás Póczos, Ruosong Wang, Keyulu Xu		code	-1
In-Place Zero-Space Memory Protection for CNN	Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, SeungHwan Lim		code	-1
Acceleration via Symplectic Discretization of High-Resolution Differential Equations	Bin Shi, Simon S. Du, Weijie J. Su, Michael I. Jordan		code	-1
XLNet: Generalized Autoregressive Pretraining for Language Understanding	Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, Quoc V. Le		code	-1
Comparison Against Task Driven Artificial Neural Networks Reveals Functional Properties in Mouse Visual Cortex	Jianghong Shi, Eric SheaBrown, Michael A. Buice		code	-1
Variance Reduced Policy Evaluation with Smooth Function Approximation	HoiTo Wai, Mingyi Hong, Zhuoran Yang, Zhaoran Wang, Kexin Tang		code	-1
Learning GANs and Ensembles Using Discrepancy	Ben Adlam, Corinna Cortes, Mehryar Mohri, Ningshan Zhang		code	-1
Co-Generation with GANs using AIS based HMC	Tiantian Fang, Alexander G. Schwing		code	-1
AttentionXML: Label Tree-based Attention-Aware Deep Model for High-Performance Extreme Multi-Label Text Classification	Ronghui You, Zihan Zhang, Ziye Wang, Suyang Dai, Hiroshi Mamitsuka, Shanfeng Zhu		code	-1
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs	Himanshu Sahni, Toby Buckley, Pieter Abbeel, Ilya Kuzovkin		code	-1
Abstract Reasoning with Distracting Features	Kecheng Zheng, ZhengJun Zha, Wei Wei		code	-1
Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer	Zhiyong Yang, Qianqian Xu, Yangbangyan Jiang, Xiaochun Cao, Qingming Huang		code	-1
Adversarial Training and Robustness for Multiple Perturbations	Florian Tramèr, Dan Boneh		code	-1
Doubly-Robust Lasso Bandit	GiSoo Kim, Myunghee Cho Paik		code	-1
DM2C: Deep Mixed-Modal Clustering	Yangbangyan Jiang, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang		code	-1
MaCow: Masked Convolutional Generative Flow	Xuezhe Ma, Xiang Kong, Shanghang Zhang, Eduard H. Hovy		code	-1
Learning by Abstraction: The Neural State Machine	Drew A. Hudson, Christopher D. Manning		code	-1
Adaptive Gradient-Based Meta-Learning Methods	Mikhail Khodak, MariaFlorina Balcan, Ameet Talwalkar		code	-1
Equipping Experts/Bandits with Long-term Memory	Kai Zheng, Haipeng Luo, Ilias Diakonikolas, Liwei Wang		code	-1
A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning	Wenhao Yang, Xiang Li, Zhihua Zhang		code	-1
Scalable inference of topic evolution via models for latent geometric structures	Mikhail Yurochkin, Zhiwei Fan, Aritra Guha, Paraschos Koutris, XuanLong Nguyen		code	-1
Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network	Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, Marius Kloft		code	-1
Deep Active Learning with a Neural Architecture Search	Yonatan Geifman, Ran ElYaniv		code	-1
Efficiently escaping saddle points on manifolds	Chris Criscitiello, Nicolas Boumal		code	-1
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks	Jiong Zhang, HsiangFu Yu, Inderjit S. Dhillon		code	-1
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters	Asiri Wijesinghe, Qing Wang		code	-1
Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning	Wonjae Kim, Yoonho Lee		code	-1
Comparing Unsupervised Word Translation Methods Step by Step	Mareike Hartmann, Yova Kementchedjhieva, Anders Søgaard		code	-1
Learning from Bad Data via Generation	Tianyu Guo, Chang Xu, Boxin Shi, Chao Xu, Dacheng Tao		code	-1
Constrained deep neural network architecture search for IoT devices accounting for hardware calibration	Florian Scheidegger, Luca Benini, Costas Bekas, A. Cristiano I. Malossi		code	-1
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection	Yihe Dong, Samuel B. Hopkins, Jerry Li		code	-1
Iterative Least Trimmed Squares for Mixed Linear Regression	Yanyao Shen, Sujay Sanghavi		code	-1
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces	Yu Qi, Bin Liu, Yueming Wang, Gang Pan		code	-1
Divergence-Augmented Policy Optimization	Qing Wang, Yingru Li, Jiechao Xiong, Tong Zhang		code	-1
Intrinsic dimension of data representations in deep neural networks	Alessio Ansuini, Alessandro Laio, Jakob H. Macke, Davide Zoccolan		code	-1
Towards a Zero-One Law for Column Subset Selection	Zhao Song, David P. Woodruff, Peilin Zhong		code	-1
Compositional De-Attention Networks	Yi Tay, Anh Tuan Luu, Aston Zhang, Shuohang Wang, Siu Cheung Hui		code	-1
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning	Jian Ni, Shanghang Zhang, Haiyong Xie		code	-1
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers	Zeyuan AllenZhu, Yuanzhi Li, Yingyu Liang		code	-1
Mining GOLD Samples for Conditional GANs	Sangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, Jinwoo Shin		code	-1
Deep Model Transferability from Attribution Maps	Jie Song, Yixin Chen, Xinchao Wang, Chengchao Shen, Mingli Song		code	-1
Fully Parameterized Quantile Function for Distributional Reinforcement Learning	Derek Yang, Li Zhao, Zichuan Lin, Tao Qin, Jiang Bian, TieYan Liu		code	-1
Direct Optimization through arg max for Discrete Variational Auto-Encoder	Guy Lorberbom, Tommi S. Jaakkola, Andreea Gane, Tamir Hazan		code	-1
Distributional Reward Decomposition for Reinforcement Learning	Zichuan Lin, Li Zhao, Derek Yang, Tao Qin, TieYan Liu, Guangwen Yang		code	-1
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise	Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang		code	-1
Convergence Guarantees for Adaptive Bayesian Quadrature Methods	Motonobu Kanagawa, Philipp Hennig		code	-1
Progressive Augmentation of GANs	Dan Zhang, Anna Khoreva		code	-1
UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization	Ali Kavis, Kfir Y. Levy, Francis R. Bach, Volkan Cevher		code	-1
Meta-Surrogate Benchmarking for Hyperparameter Optimization	Aaron Klein, Zhenwen Dai, Frank Hutter, Neil D. Lawrence, Javier Gonzalez		code	-1
Learning to Perform Local Rewriting for Combinatorial Optimization	Xinyun Chen, Yuandong Tian		code	-1
Anti-efficient encoding in emergent communication	Rahma Chaabouni, Eugene Kharitonov, Emmanuel Dupoux, Marco Baroni		code	-1
Singleshot : a scalable Tucker tensor decomposition	Abraham Traoré, Maxime Berar, Alain Rakotomamonjy		code	-1
Neural Machine Translation with Soft Prototype	Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, ChengXiang Zhai, TieYan Liu		code	-1
Reliable training and estimation of variance networks	Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg		code	-1
Copula Multi-label Learning	Weiwei Liu		code	-1
Bayesian Learning of Sum-Product Networks	Martin Trapp, Robert Peharz, Hong Ge, Franz Pernkopf, Zoubin Ghahramani		code	-1
Bayesian Batch Active Learning as Sparse Subset Approximation	Robert Pinsler, Jonathan Gordon, Eric T. Nalisnick, José Miguel HernándezLobato		code	-1
Optimal Sparsity-Sensitive Bounds for Distributed Mean Estimation	Zengfeng Huang, Ziyue Huang, Yilei Wang, Ke Yi		code	-1
Global Sparse Momentum SGD for Pruning Very Deep Neural Networks	Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, Ji Liu		code	-1
Variational Bayesian Decision-making for Continuous Utilities	Tomasz Kusmierczyk, Joseph Sakaya, Arto Klami		code	-1
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks	Ryo Karakida, Shotaro Akaho, Shunichi Amari		code	-1
Single-Model Uncertainties for Deep Learning	Natasa Tagasovska, David LopezPaz		code	-1
Is Deeper Better only when Shallow is Good?	Eran Malach, Shai ShalevShwartz		code	-1
Wasserstein Weisfeiler-Lehman Graph Kernels	Matteo Togninalli, M. Elisabetta Ghisu, Felipe LlinaresLópez, Bastian Rieck, Karsten M. Borgwardt		code	-1
Domain Generalization via Model-Agnostic Learning of Semantic Features	Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker		code	-1
Grid Saliency for Context Explanations of Semantic Segmentation	Lukas Hoyer, Mauricio Munoz, Prateek Katiyar, Anna Khoreva, Volker Fischer		code	-1
First-order methods almost always avoid saddle points: The case of vanishing step-sizes	Ioannis Panageas, Georgios Piliouras, Xiao Wang		code	-1
Maximum Mean Discrepancy Gradient Flow	Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton		code	-1
Oblivious Sampling Algorithms for Private Data Analysis	Sajin Sasy, Olga Ohrimenko		code	-1
Semi-supervisedly Co-embedding Attributed Networks	Zaiqiao Meng, Shangsong Liang, Jinyuan Fang, Teng Xiao		code	-1
From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI	Roman Beliy, Guy Gaziv, Assaf Hoogi, Francesca Strappini, Tal Golan, Michal Irani		code	-1
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders	Natasa Tagasovska, Damien Ackerer, Thibault Vatter		code	-1
Nonstochastic Multiarmed Bandits with Unrestricted Delays	Tobias Sommer Thune, Nicolò CesaBianchi, Yevgeny Seldin		code	-1
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling	Lars Maaløe, Marco Fraccaro, Valentin Liévin, Ole Winther		code	-1
Code Generation as a Dual Task of Code Summarization	Bolin Wei, Ge Li, Xin Xia, Zhiyi Fu, Zhi Jin		code	-1
Diffeomorphic Temporal Alignment Nets	Ron Shapira Weber, Matan Eyal, Nicki Skafte Detlefsen, Oren Shriki, Oren Freifeld		code	-1
Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior	ChengChun Hsu, KuangJui Hsu, ChungChi Tsai, YenYu Lin, YungYu Chuang		code	-1
On the Power and Limitations of Random Features for Understanding Neural Networks	Gilad Yehudai, Ohad Shamir		code	-1
Efficient Pure Exploration in Adaptive Round model	Tianyuan Jin, Jieming Shi, Xiaokui Xiao, Enhong Chen		code	-1
Multi-objects Generation with Amortized Structural Regularization	Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang		code	-1
Neural Shuffle-Exchange Networks - Sequence Processing in O(n log n) Time	Karlis Freivalds, Emils Ozolins, Agris Sostaks		code	-1
DetNAS: Backbone Search for Object Detection	Yukang Chen, Tong Yang, Xiangyu Zhang, Gaofeng Meng, Xinyu Xiao, Jian Sun		code	-1
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates	Adil Salim, Dmitry Kovalev, Peter Richtárik		code	-1
Fast AutoAugment	Sungbin Lim, Ildoo Kim, Taesup Kim, Chiheon Kim, Sungwoong Kim		code	-1
On the Convergence Rate of Training Recurrent Neural Networks	Zeyuan AllenZhu, Yuanzhi Li, Zhao Song		code	-1
Interval timing in deep reinforcement learning agents	Ben Deverett, Ryan Faulkner, Meire Fortunato, Gregory Wayne, Joel Z. Leibo		code	-1
Graph-based Discriminators: Sample Complexity and Expressiveness	Roi Livni, Yishay Mansour		code	-1
Large Scale Structure of Neural Network Loss Landscapes	Stanislav Fort, Stanislaw Jastrzebski		code	-1
Learning Nonsymmetric Determinantal Point Processes	Mike Gartrell, VictorEmmanuel Brunel, Elvis Dohmatob, Syrine Krichene		code	-1
Hypothesis Set Stability and Generalization	Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan		code	-1
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds	Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang, Andrew Markham, Niki Trigoni		code	-1
Precision-Recall Balanced Topic Modelling	Seppo Virtanen, Mark A. Girolami		code	-1
Learning Sparse Distributions using Iterative Hard Thresholding	Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo		code	-1
Discriminative Topic Modeling with Logistic LDA	Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis		code	-1
Quantum Wasserstein Generative Adversarial Networks	Shouvanik Chakrabarti, Yiming Huang, Tongyang Li, Soheil Feizi, Xiaodi Wu		code	-1
Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion	Joan Serrà, Santiago Pascual, Carlos Segura		code	-1
Hyperparameter Learning via Distributional Transfer	Ho Chung Leon Law, Peilin Zhao, Leung Sing Chan, Junzhou Huang, Dino Sejdinovic		code	-1
Discriminator optimal transport	Akinori Tanaka		code	-1
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes	David Salinas, Michael BohlkeSchneider, Laurent Callot, Roberto Medico, Jan Gasthaus		code	-1
Are Anchor Points Really Indispensable in Label-Noise Learning?	Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama		code	-1
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations	Fenglin Liu, Yuanxin Liu, Xuancheng Ren, Xiaodong He, Xu Sun		code	-1
Differentiable Ranking and Sorting using Optimal Transport	Marco Cuturi, Olivier Teboul, JeanPhilippe Vert		code	-1
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks	Gaël Letarte, Pascal Germain, Benjamin Guedj, François Laviolette		code	-1
Likelihood-Free Overcomplete ICA and Applications In Causal Discovery	Chenwei Ding, Mingming Gong, Kun Zhang, Dacheng Tao		code	-1
Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem	Dongdong Ge, Haoyue Wang, Zikai Xiong, Yinyu Ye		code	-1
Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs	Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko		code	-1
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections	Boris Muzellec, Marco Cuturi		code	-1
Efficient Smooth Non-Convex Stochastic Compositional Optimization via Stochastic Recursive Gradient Descent	Huizhuo Yuan, Xiangru Lian, Chris Junchi Li, Ji Liu, Wenqing Hu		code	-1
On the convergence of single-call stochastic extra-gradient methods	YuGuan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos		code	-1
Infra-slow brain dynamics as a marker for cognitive function and decline	Shagun Ajmera, Shreya Rajagopal, Razi Rehman, Devarajan Sridharan		code	-1
Robust Principal Component Analysis with Adaptive Neighbors	Rui Zhang, Hanghang Tong		code	-1
High-Quality Self-Supervised Deep Image Denoising	Samuli Laine, Tero Karras, Jaakko Lehtinen, Timo Aila		code	-1
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup	Sebastian Goldt, Madhu Advani, Andrew M. Saxe, Florent Krzakala, Lenka Zdeborová		code	-1
GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs	Yuan Liu, Zehong Shen, Zhixuan Lin, Sida Peng, Hujun Bao, Xiaowei Zhou		code	-1
Online Prediction of Switching Graph Labelings with Cluster Specialists	Mark Herbster, James Robinson		code	-1
Graph-Based Semi-Supervised Learning with Non-ignorable Non-response	Fan Zhou, Tengfei Li, Haibo Zhou, Hongtu Zhu, Jieping Ye		code	-1
BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning	Andreas Kirsch, Joost van Amersfoort, Yarin Gal		code	-1
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off	Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry		code	-1
Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs	Marek Petrik, Reazul Hasan Russel		code	-1
Cross-lingual Language Model Pretraining	Alexis Conneau, Guillaume Lample		code	-1
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse	Cornelius Schröder, Ben James, Leon Lagnado, Philipp Berens		code	-1
Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input	Maxence Ernoult, Julie Grollier, Damien Querlioz, Yoshua Bengio, Benjamin Scellier		code	-1
Universal Invariant and Equivariant Graph Neural Networks	Nicolas Keriven, Gabriel Peyré		code	-1
Are sample means in multi-armed bandits positively or negatively biased?	Jaehyeok Shin, Aaditya Ramdas, Alessandro Rinaldo		code	-1
On the Correctness and Sample Complexity of Inverse Reinforcement Learning	Abi Komanduru, Jean Honorio		code	-1
VIREL: A Variational Inference Framework for Reinforcement Learning	Matthew Fellows, Anuj Mahajan, Tim G. J. Rudner, Shimon Whiteson		code	-1
First Order Motion Model for Image Animation	Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov, Elisa Ricci, Nicu Sebe		code	-1
Tensor Monte Carlo: Particle Methods for the GPU era	Laurence Aitchison		code	-1
Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction	Alban Laflaquière, Michaël Garcia Ortiz		code	-1
Learning from Label Proportions with Generative Adversarial Networks	Jiabin Liu, Bo Wang, Zhiquan Qi, Yingjie Tian, Yong Shi		code	-1
Efficient and Thrifty Voting by Any Means Necessary	Debmalya Mandal, Ariel D. Procaccia, Nisarg Shah, David P. Woodruff		code	-1
PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation	Can Qin, Haoxuan You, Lichen Wang, C.C. Jay Kuo, Yun Fu		code	-1
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization	Xiangyi Chen, Sijia Liu, Kaidi Xu, Xingguo Li, Xue Lin, Mingyi Hong, David D. Cox		code	-1
Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning	Erwan Lecarpentier, Emmanuel Rachelson		code	-1
Depth-First Proof-Number Search with Heuristic Edge Cost and Application to Chemical Synthesis Planning	Akihiro Kishimoto, Beat Buesser, Bei Chen, Adi Botea		code	-1
Toward a Characterization of Loss Functions for Distribution Learning	Nika Haghtalab, Cameron Musco, Bo Waggoner		code	-1
Coresets for Archetypal Analysis	Sebastian Mair, Ulf Brefeld		code	-1
Emergence of Object Segmentation in Perturbed Generative Models	Adam Bielski, Paolo Favaro		code	-1
Optimal Sparse Decision Trees	Xiyang Hu, Cynthia Rudin, Margo I. Seltzer		code	-1
Escaping from saddle points on Riemannian manifolds	Yue Sun, Nicolas Flammarion, Maryam Fazel		code	-1
Multi-source Domain Adaptation for Semantic Segmentation	Sicheng Zhao, Bo Li, Xiangyu Yue, Yang Gu, Pengfei Xu, Runbo Hu, Hua Chai, Kurt Keutzer		code	-1
Localized Structured Prediction	Carlo Ciliberto, Francis R. Bach, Alessandro Rudi		code	-1
Nonzero-sum Adversarial Hypothesis Testing Games	Sarath Yasodharan, Patrick Loiseau		code	-1
Manifold-regression to predict from MEG/EEG brain signals without source modeling	David Sabbagh, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, Denis A. Engemann		code	-1
Modeling Tabular data using Conditional GAN	Lei Xu, Maria Skoularidou, Alfredo CuestaInfante, Kalyan Veeramachaneni		code	-1
Normalization Helps Training of Quantized LSTM	Lu Hou, Jinhua Zhu, James T. Kwok, Fei Gao, Tao Qin, TieYan Liu		code	-1
Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration	Clarice Poon, Jingwei Liang		code	-1
Deep Scale-spaces: Equivariance Over Scale	Daniel E. Worrall, Max Welling		code	-1
GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series	Edward De Brouwer, Jaak Simm, Adam Arany, Yves Moreau		code	-1
Estimating Convergence of Markov chains with L-Lag Couplings	Niloy Biswas, Pierre E. Jacob, Paul Vanetti		code	-1
Learning-Based Low-Rank Approximations	Piotr Indyk, Ali Vakilian, Yang Yuan		code	-1
Implicit Regularization in Deep Matrix Factorization	Sanjeev Arora, Nadav Cohen, Wei Hu, Yuping Luo		code	-1
List-decodable Linear Regression	Sushrut Karmalkar, Adam R. Klivans, Pravesh Kothari		code	-1
Learning elementary structures for 3D shape generation and matching	Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, Mathieu Aubry		code	-1
On the Hardness of Robust Classification	Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell		code	-1
Foundations of Comparison-Based Hierarchical Clustering	Debarghya Ghoshdastidar, Michaël Perrot, Ulrike von Luxburg		code	-1
What the Vec? Towards Probabilistically Grounded Embeddings	Carl Allen, Ivana Balazevic, Timothy M. Hospedales		code	-1
Minimizers of the Empirical Risk and Risk Monotonicity	Marco Loog, Tom J. Viering, Alexander Mey		code	-1
Explicit Planning for Efficient Exploration in Reinforcement Learning	Liangpeng Zhang, Ke Tang, Xin Yao		code	-1
Lower Bounds on Adversarial Robustness from Optimal Transport	Arjun Nitin Bhagoji, Daniel Cullina, Prateek Mittal		code	-1
Neural Spline Flows	Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios		code	-1
Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints	David SimchiLevi, Yunzong Xu		code	-1
Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization	Koen Helwegen, James Widdicombe, Lukas Geiger, Zechun Liu, KwangTing Cheng, Roeland Nusselder		code	-1
Nonlinear scaling of resource allocation in sensory bottlenecks	Laura Rose Edmondson, Alejandro JiménezRodríguez, Hannes P. Saal		code	-1
Constrained Reinforcement Learning Has Zero Duality Gap	Santiago Paternain, Luiz F. O. Chamon, Miguel CalvoFullana, Alejandro Ribeiro		code	-1
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules	Niklas W. A. Gebauer, Michael Gastegger, Kristof Schütt		code	-1
An adaptive nearest neighbor rule for classification	Akshay Balsubramani, Sanjoy Dasgupta, Yoav Freund, Shay Moran		code	-1
Coresets for Clustering with Fairness Constraints	Lingxiao Huang, Shaofeng H.C. Jiang, Nisheeth K. Vishnoi		code	-1
PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments	David Novotný, Benjamin Graham, Jeremy Reizenstein		code	-1
MAVEN: Multi-Agent Variational Exploration	Anuj Mahajan, Tabish Rashid, Mikayel Samvelyan, Shimon Whiteson		code	-1
Competitive Gradient Descent	Florian Schäfer, Anima Anandkumar		code	-1
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses	Ulysse MarteauFerey, Francis R. Bach, Alessandro Rudi		code	-1
Continual Unsupervised Representation Learning	Dushyant Rao, Francesco Visin, Andrei A. Rusu, Razvan Pascanu, Yee Whye Teh, Raia Hadsell		code	-1
Self-Routing Capsule Networks	Taeyoung Hahn, Myeongjang Pyeon, Gunhee Kim		code	-1
The Parameterized Complexity of Cascading Portfolio Scheduling	Eduard Eiben, Robert Ganian, Iyad Kanj, Stefan Szeider		code	-1
Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards	Falcon Z. Dai, Matthew R. Walter		code	-1
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes	Rishidev Chaudhuri, Ila Fiete		code	-1
Sequence Modeling with Unconstrained Generation Order	Dmitrii Emelianenko, Elena Voita, Pavel Serdyukov		code	-1
Probabilistic Logic Neural Networks for Reasoning	Meng Qu, Jian Tang		code	-1
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families	Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant		code	-1
A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening	Gecia Bravo Hermsdorff, Lee M. Gunderson		code	-1
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond	Xuechen Li, Yi Wu, Lester Mackey		code	-1
The Implicit Bias of AdaGrad on Separable Data	Qian Qian, Xiaoyuan Qian		code	-1
On two ways to use determinantal point processes for Monte Carlo integration	Guillaume Gautier, Rémi Bardenet, Michal Valko		code	-1
LiteEval: A Coarse-to-Fine Framework for Resource Efficient Video Recognition	Zuxuan Wu, Caiming Xiong, YuGang Jiang, Larry S. Davis		code	-1
How degenerate is the parametrization of neural networks with the ReLU activation function?	Dennis Elbrächter, Julius Berner, Philipp Grohs		code	-1
Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks	Wenrui Zhang, Peng Li		code	-1
Re-examination of the Role of Latent Variables in Sequence Modeling	Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo		code	-1
Max-value Entropy Search for Multi-Objective Bayesian Optimization	Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa		code	-1
Stein Variational Gradient Descent With Matrix-Valued Kernels	Dilin Wang, Ziyang Tang, Chandrajit Bajaj, Qiang Liu		code	-1
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms	Shahana Ibrahim, Xiao Fu, Nikolaos Kargas, Kejun Huang		code	-1
Detecting Overfitting via Adversarial Examples	Roman Werpachowski, András György, Csaba Szepesvári		code	-1
A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment	Felix Leibfried, Sergio PascualDiaz, Jordi GrauMoya		code	-1
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies	Seyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard S. Zemel		code	-1
Towards Understanding the Importance of Shortcut Connections in Residual Networks	Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao		code	-1
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains	Elliot Meyerson, Risto Miikkulainen		code	-1
Solving Interpretable Kernel Dimensionality Reduction	Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy		code	-1
Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space	Shuo Yang, Yanyao Shen, Sujay Sanghavi		code	-1
A Model to Search for Synthesizable Molecules	John Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel HernándezLobato		code	-1
Post training 4-bit quantization of convolutional networks for rapid-deployment	Ron Banner, Yury Nahshan, Daniel Soudry		code	-1
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes	James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner		code	-1
Differentially Private Anonymized Histograms	Ananda Theertha Suresh		code	-1
Dynamic Local Regret for Non-convex Online Forecasting	Sergül Aydöre, Tianhao Zhu, Dean P. Foster		code	-1
Learning Local Search Heuristics for Boolean Satisfiability	Emre Yolcu, Barnabás Póczos		code	-1
Provably Efficient Q-Learning with Low Switching Cost	Yu Bai, Tengyang Xie, Nan Jiang, YuXiang Wang		code	-1
Solving graph compression via optimal transport	Vikas K. Garg, Tommi S. Jaakkola		code	-1
PyTorch: An Imperative Style, High-Performance Deep Learning Library	Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala		code	-1
Stability of Graph Scattering Transforms	Fernando Gama, Alejandro Ribeiro, Joan Bruna		code	-1
A Debiased MDI Feature Importance Measure for Random Forests	Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu		code	-1
Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle	Simon S. Du, Yuping Luo, Ruosong Wang, Hanrui Zhang		code	-1
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models	Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis		code	-1
Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks	Guodong Zhang, James Martens, Roger B. Grosse		code	-1
Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices	Santosh S. Vempala, Andre Wibisono		code	-1
Learning Distributions Generated by One-Layer ReLU Networks	Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi		code	-1
Large-scale optimal transport map estimation using projection pursuit	Cheng Meng, Yuan Ke, Jingyi Zhang, Mengrui Zhang, Wenxuan Zhong, Ping Ma		code	-1
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning	Nicolas Carion, Nicolas Usunier, Gabriel Synnaeve, Alessandro Lazaric		code	-1
On Exact Computation with an Infinitely Wide Neural Net	Sanjeev Arora, Simon S. Du, Wei Hu, Zhiyuan Li, Ruslan Salakhutdinov, Ruosong Wang		code	-1
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning	Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster		code	-1
Chirality Nets for Human Pose Regression	Raymond A. Yeh, YuanTing Hu, Alexander G. Schwing		code	-1
Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds	Minshuo Chen, Haoming Jiang, Wenjing Liao, Tuo Zhao		code	-1
Fast Decomposable Submodular Function Minimization using Constrained Total Variation	Senanayak Sesh Kumar Karri, Francis R. Bach, Thomas Pock		code	-1
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model	Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse		code	-1
Spherical Text Embedding	Yu Meng, Jiaxin Huang, Guangyuan Wang, Chao Zhang, Honglei Zhuang, Lance M. Kaplan, Jiawei Han		code	-1
Möbius Transformation for Fast Inner Product Search on Graph	Zhixin Zhou, Shulong Tan, Zhaozhuo Xu, Ping Li		code	-1
Hyperbolic Graph Neural Networks	Qi Liu, Maximilian Nickel, Douwe Kiela		code	-1
Average Individual Fairness: Algorithms, Generalization and Experiments	Saeed SharifiMalvajerdi, Michael J. Kearns, Aaron Roth		code	-1
Fixing the train-test resolution discrepancy	Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou		code	-1
Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes	Lingge Li, Dustin S. Pluta, Babak Shahbaba, Norbert Fortin, Hernando Ombao, Pierre Baldi		code	-1
Manipulating a Learning Defender and Ways to Counteract	Jiarui Gan, Qingyu Guo, Long TranThanh, Bo An, Michael J. Wooldridge		code	-1
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations	Andrew Spielberg, Allan Zhao, Yuanming Hu, Tao Du, Wojciech Matusik, Daniela Rus		code	-1
Learning to Infer Implicit Surfaces without 3D Supervision	Shichen Liu, Shunsuke Saito, Weikai Chen, Hao Li		code	-1
Fast and Accurate Least-Mean-Squares Solvers	Alaa Maalouf, Ibrahim Jubran, Dan Feldman		code	-1
Certifiable Robustness to Graph Perturbations	Aleksandar Bojchevski, Stephan Günnemann		code	-1
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay	Frederic Koehler		code	-1
Paradoxes in Fair Machine Learning	Paul Gölz, Anson Kahng, Ariel D. Procaccia		code	-1
Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost	Zhuoran Yang, Yongxin Chen, Mingyi Hong, Zhaoran Wang		code	-1
The spiked matrix model with generative priors	Benjamin Aubin, Bruno Loureiro, Antoine Maillard, Florent Krzakala, Lenka Zdeborová		code	-1
Gradient Dynamics of Shallow Univariate ReLU Networks	Francis Williams, Matthew Trager, Daniele Panozzo, Cláudio T. Silva, Denis Zorin, Joan Bruna		code	-1
Robust and Communication-Efficient Collaborative Learning	Amirhossein Reisizadeh, Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani		code	-1
Multiclass Learning from Contradictions	Sauptik Dhar, Vladimir Cherkassky, Mohak Shah		code	-1
Learning from Trajectories via Subgoal Discovery	Sujoy Paul, Jeroen van Baar, Amit K. RoyChowdhury		code	-1
Distributed Low-rank Matrix Factorization With Exact Consensus	Zhihui Zhu, Qiuwei Li, Xinshuo Yang, Gongguo Tang, Michael B. Wakin		code	-1
Online Normalization for Training Neural Networks	Vitaliy Chiley, Ilya Sharapov, Atli Kosson, Urs Köster, Ryan Reece, Sofia Samaniego de la Fuente, Vishal Subbiah, Michael James		code	-1
The Synthesis of XNOR Recurrent Neural Networks with Stochastic Logic	Arash Ardakani, Zhengyun Ji, Amir Ardakani, Warren J. Gross		code	-1
An adaptive Mirror-Prox method for variational inequalities with singular operators	Kimon Antonakopoulos, Elena Veronica Belmega, Panayotis Mertikopoulos		code	-1
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules	Shengchao Liu, Mehmet Furkan Demirel, Yingyu Liang		code	-1
Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory	Bin Hu, Usman Ahmed Syed		code	-1
Facility Location Problem in Differential Privacy Model Revisited	Yunus Esencayi, Marco Gaboardi, Shi Li, Di Wang		code	-1
Energy-Inspired Models: Learning with Sampler-Induced Distributions	Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath		code	-1
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator	Karl Krauth, Stephen Tu, Benjamin Recht		code	-1
A Universally Optimal Multistage Accelerated Stochastic Gradient Method	Necdet Serhat Aybat, Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar		code	-1
From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction	Hidenori Tanaka, Aran Nayebi, Niru Maheswaranathan, Lane McIntosh, Stephen Baccus, Surya Ganguli		code	-1
Large Memory Layers with Product Keys	Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou		code	-1
Learning Deterministic Weighted Automata with Queries and Counterexamples	Gail Weiss, Yoav Goldberg, Eran Yahav		code	-1
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent	Jaehoon Lee, Lechao Xiao, Samuel S. Schoenholz, Yasaman Bahri, Roman Novak, Jascha SohlDickstein, Jeffrey Pennington		code	-1
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals	Surbhi Goel, Sushrut Karmalkar, Adam R. Klivans		code	-1
Visualizing and Measuring the Geometry of BERT	Emily Reif, Ann Yuan, Martin Wattenberg, Fernanda B. Viégas, Andy Coenen, Adam Pearce, Been Kim		code	-1
Self-Critical Reasoning for Robust Visual Question Answering	Jialin Wu, Raymond J. Mooney		code	-1
Learning to Screen	Alon Cohen, Avinatan Hassidim, Haim Kaplan, Yishay Mansour, Shay Moran		code	-1
A Communication Efficient Stochastic Multi-Block Alternating Direction Method of Multipliers	Hao Yu		code	-1
A Little Is Enough: Circumventing Defenses For Distributed Learning	Gilad Baruch, Moran Baruch, Yoav Goldberg		code	-1
Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks	Gunjan Verma, Ananthram Swami		code	-1
A Robust Non-Clairvoyant Dynamic Mechanism for Contextual Auctions	Yuan Deng, Sébastien Lahaie, Vahab S. Mirrokni		code	-1
Finite-Sample Analysis for SARSA with Linear Function Approximation	Shaofeng Zou, Tengyu Xu, Yingbin Liang		code	-1
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models	Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová		code	-1
Graph Structured Prediction Energy Networks	Colin Graber, Alexander G. Schwing		code	-1
Private Learning Implies Online Learning: An Efficient Reduction	Alon Gonen, Elad Hazan, Shay Moran		code	-1
Graph Agreement Models for Semi-Supervised Learning	Otilia Stretcu, Krishnamurthy Viswanathan, Dana MovshovitzAttias, Emmanouil A. Platanios, Sujith Ravi, Andrew Tomkins		code	-1
Latent distance estimation for random geometric graphs	Ernesto Araya Valdivia, Yohann de Castro		code	-1
Seeing the Wind: Visual Wind Speed Prediction with a Coupled Convolutional and Recurrent Neural Network	Jennifer L. Cardona, Michael F. Howland, John O. Dabiri		code	-1
The Functional Neural Process	Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling		code	-1
Recurrent Registration Neural Networks for Deformable Image Registration	Robin Sandkühler, Simon Andermatt, Grzegorz Bauman, Sylvia Nyilas, Christoph Jud, Philippe C. Cattin		code	-1
Unsupervised State Representation Learning in Atari	Ankesh Anand, Evan Racah, Sherjil Ozair, Yoshua Bengio, MarcAlexandre Côté, R. Devon Hjelm		code	-1
Unlocking Fairness: a Trade-off Revisited	Michael L. Wick, Swetasudha Panda, JeanBaptiste Tristan		code	-1
Fisher Efficient Inference of Intractable Models	Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen		code	-1
Thompson Sampling and Approximate Inference	My Phan, Yasin AbbasiYadkori, Justin Domke		code	-1
PRNet: Self-Supervised Learning for Partial-to-Partial Registration	Yue Wang, Justin M. Solomon		code	-1
Surrogate Objectives for Batch Policy Optimization in One-step Decision Making	Minmin Chen, Ramki Gummadi, Chris Harris, Dale Schuurmans		code	-1
Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians	Axel Brando, José A. RodríguezSerrano, Jordi Vitrià, Alberto Rubio		code	-1
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization	Farzane Aminmansour, Andrew Patterson, Lei Le, Yisu Peng, Daniel Mitchell, Franco Pestilli, Cesar F. Caiafa, Russell Greiner, Martha White		code	-1
Approximating the Permanent by Sampling from Adaptive Partitions	Jonathan Kuck, Tri Dao, Hamid Rezatofighi, Ashish Sabharwal, Stefano Ermon		code	-1
Retrosynthesis Prediction with Conditional Graph Logic Network	Hanjun Dai, Chengtao Li, Connor W. Coley, Bo Dai, Le Song		code	-1
Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration	Robert Kleinberg, Kevin LeytonBrown, Brendan Lucier, Devon R. Graham		code	-1
Online Learning via the Differential Privacy Lens	Jacob D. Abernethy, Young Hun Jung, Chansoo Lee, Audra McMillan, Ambuj Tewari		code	-1
PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points	Siyuan Huang, Yixin Chen, Tao Yuan, Siyuan Qi, Yixin Zhu, SongChun Zhu		code	-1
Parameter elimination in particle Gibbs sampling	Anna Wigren, Riccardo Sven Risuleo, Lawrence Murray, Fredrik Lindsten		code	-1
This Looks Like That: Deep Learning for Interpretable Image Recognition	Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan Su		code	-1
Adaptively Aligned Image Captioning via Adaptive Attention Time	Lun Huang, Wenmin Wang, Yaxian Xia, Jie Chen		code	-1
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning	Jeremiah Z. Liu, John W. Paisley, MarianthiAnna Kioumourtzoglou, Brent A. Coull		code	-1
Learning Bayesian Networks with Low Rank Conditional Probability Tables	Adarsh Barik, Jean Honorio		code	-1
Equal Opportunity in Online Classification with Partial Feedback	Yahav Bechavod, Katrina Ligett, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu		code	-1
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations	Kevin Smith, Lingjie Mei, Shunyu Yao, Jiajun Wu, Elizabeth S. Spelke, Josh Tenenbaum, Tomer D. Ullman		code	-1
Neural Multisensory Scene Inference	Jae Hyun Lim, Pedro O. Pinheiro, Negar Rostamzadeh, Chris Pal, Sungjin Ahn		code	-1
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems	Young Hun Jung, Ambuj Tewari		code	-1
What Can ResNet Learn Efficiently, Going Beyond Kernels?	Zeyuan AllenZhu, Yuanzhi Li		code	-1
Better Transfer Learning with Inferred Successor Maps	Tamas Madarasz, Tim E. J. Behrens		code	-1
Unsupervised Co-Learning on G-Manifolds Across Irreducible Representations	Yifeng Fan, Tingran Gao, Zhizhen Zhao		code	-1
Defending Against Neural Fake News	Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, Yejin Choi		code	-1
Sample Adaptive MCMC	Michael Zhu		code	-1
A Stochastic Composite Gradient Method with Incremental Variance Reduction	Junyu Zhang, Lin Xiao		code	-1
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses	Ananya Uppal, Shashank Singh, Barnabás Póczos		code	-1
STAR-Caps: Capsule Networks with Straight-Through Attentive Routing	Karim Ahmed, Lorenzo Torresani		code	-1
Limitations of Lazy Training of Two-layers Neural Network	Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari		code	-1
Reconciling meta-learning and continual learning with online mixtures of tasks	Ghassen Jerfel, Erin Grant, Tom Griffiths, Katherine A. Heller		code	-1
Distributionally Robust Optimization and Generalization in Kernel Methods	Matthew Staib, Stefanie Jegelka		code	-1
A General Theory of Equivariant CNNs on Homogeneous Spaces	Taco S. Cohen, Mario Geiger, Maurice Weiler		code	-1
Trivializations for Gradient-Based Optimization on Manifolds	Mario Lezcano Casado		code	-1
Write, Execute, Assess: Program Synthesis with a REPL	Kevin Ellis, Maxwell I. Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando SolarLezama		code	-1
A Meta-Analysis of Overfitting in Machine Learning	Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht, Sara FridovichKeil, Moritz Hardt, John Miller, Ludwig Schmidt		code	-1
(Nearly) Efficient Algorithms for the Graph Matching Problem on Correlated Random Graphs	Boaz Barak, ChiNing Chou, Zhixian Lei, Tselil Schramm, Yueqi Sheng		code	-1
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models	Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin (Jerry) Zhu, Adish Singla		code	-1
Online Continuous Submodular Maximization: From Full-Information to Bandit Feedback	Mingrui Zhang, Lin Chen, Hamed Hassani, Amin Karbasi		code	-1
Sampling Networks and Aggregate Simulation for Online POMDP Planning	Hao Cui, Roni Khardon		code	-1
Correlation in Extensive-Form Games: Saddle-Point Formulation and Benchmarks	Gabriele Farina, Chun Kai Ling, Fei Fang, Tuomas Sandholm		code	-1
GNNExplainer: Generating Explanations for Graph Neural Networks	Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec		code	-1
Linear Stochastic Bandits Under Safety Constraints	Sanae Amani, Mahnoosh Alizadeh, Christos Thrampoulidis		code	-1
A coupled autoencoder approach for multi-modal analysis of cell types	Rohan Gala, Nathan Gouwens, Zizhen Yao, Agata Budzillo, Osnat Penn, Bosiljka Tasic, Gabe Murphy, Hongkui Zeng, Uygar Sümbül		code	-1
Towards Automatic Concept-based Explanations	Amirata Ghorbani, James Wexler, James Y. Zou, Been Kim		code	-1
Deep Generative Video Compression	Salvator Lombardo, Jun Han, Christopher Schroers, Stephan Mandt		code	-1
Budgeted Reinforcement Learning in Continuous State Space	Nicolas Carrara, Edouard Leurent, Romain Laroche, Tanguy Urvoy, OdalricAmbrym Maillard, Olivier Pietquin		code	-1
Discovery of Useful Questions as Auxiliary Tasks	Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh		code	-1
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm	Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto		code	-1
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias	Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Joan Bruna		code	-1
Correlation clustering with local objectives	Sanchit Kalhan, Konstantin Makarychev, Timothy Zhou		code	-1
Multiclass Performance Metric Elicitation	Gaurush Hiranandani, Shant Boodaghians, Ruta Mehta, Oluwasanmi Koyejo		code	-1
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing	Zhiqi Bu, Jason M. Klusowski, Cynthia Rush, Weijie J. Su		code	-1
Explicit Explore-Exploit Algorithms in Continuous State Spaces	Mikael Henaff		code	-1
ADDIS: an adaptive discarding algorithm for online FDR control with conservative nulls	Jinjin Tian, Aaditya Ramdas		code	-1
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices	Vincent S. Chen, Sen Wu, Alexander J. Ratner, Jen Weng, Christopher Ré		code	-1
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse	James Lucas, George Tucker, Roger B. Grosse, Mohammad Norouzi		code	-1
Language as an Abstraction for Hierarchical Deep Reinforcement Learning	Yiding Jiang, Shixiang Gu, Kevin Murphy, Chelsea Finn		code	-1
Efficient online learning with kernels for adversarial large scale problems	Rémi Jézéquel, Pierre Gaillard, Alessandro Rudi		code	-1
A Linearly Convergent Method for Non-Smooth Non-Convex Optimization on the Grassmannian with Applications to Robust Subspace and Dictionary Learning	Zhihui Zhu, Tianyu Ding, Daniel P. Robinson, Manolis C. Tsakiris, René Vidal		code	-1
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models	Andrei Barbu, David Mayo, Julian Alverio, William Luo, Christopher Wang, Dan Gutfreund, Josh Tenenbaum, Boris Katz		code	-1
Certified Adversarial Robustness with Additive Noise	Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin		code	-1
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels	Michela Meister, Tamás Sarlós, David P. Woodruff		code	-1
Non-Cooperative Inverse Reinforcement Learning	Xiangyuan Zhang, Kaiqing Zhang, Erik Miehling, Tamer Basar		code	-1
DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization	Rixon Crane, Fred Roosta		code	-1
Sobolev Independence Criterion	Youssef Mroueh, Tom Sercu, Mattia Rigotti, Inkit Padhi, Cícero Nogueira dos Santos		code	-1
Maximum Entropy Monte-Carlo Planning	Chenjun Xiao, Ruitong Huang, Jincheng Mei, Dale Schuurmans, Martin Müller		code	-1
Learning from brains how to regularize machines	Zhe Li, Wieland Brendel, Edgar Y. Walker, Erick Cobos, Taliah Muhammad, Jacob Reimer, Matthias Bethge, Fabian H. Sinz, Zachary Pitkow, Andreas S. Tolias		code	-1
Using Statistics to Automate Stochastic Optimization	Hunter Lang, Lin Xiao, Pengchuan Zhang		code	-1
Zero-shot Knowledge Transfer via Adversarial Belief Matching	Paul Micaelli, Amos J. Storkey		code	-1
Differentiable Convex Optimization Layers	Akshay Agrawal, Brandon Amos, Shane T. Barratt, Stephen P. Boyd, Steven Diamond, J. Zico Kolter		code	-1
Random Tessellation Forests	Shufei Ge, Shijia Wang, Yee Whye Teh, Liangliang Wang, Lloyd T. Elliott		code	-1
Learning Nearest Neighbor Graphs from Noisy Distance Samples	Blake Mason, Ardhendu Tripathy, Robert D. Nowak		code	-1
Lookahead Optimizer: k steps forward, 1 step back	Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton		code	-1
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer	Wenzheng Chen, Huan Ling, Jun Gao, Edward J. Smith, Jaakko Lehtinen, Alec Jacobson, Sanja Fidler		code	-1
Covariate-Powered Empirical Bayes Estimation	Nikolaos Ignatiadis, Stefan Wager		code	-1
Understanding the Role of Momentum in Stochastic Gradient Methods	Igor Gitman, Hunter Lang, Pengchuan Zhang, Lin Xiao		code	-1
A neurally plausible model for online recognition and postdiction in a dynamical environment	Li Kevin Wenliang, Maneesh Sahani		code	-1
Guided Meta-Policy Search	Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn		code	-1
Towards Optimal Off-Policy Evaluation for Reinforcement Learning with Marginalized Importance Sampling	Tengyang Xie, Yifei Ma, YuXiang Wang		code	-1
Contextual Bandits with Cross-Learning	Santiago R. Balseiro, Negin Golrezaei, Mohammad Mahdian, Vahab S. Mirrokni, Jon Schneider		code	-1
Evaluating Protein Transfer Learning with TAPE	Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John F. Canny, Pieter Abbeel, Yun S. Song		code	-1
A Bayesian Theory of Conformity in Collective Decision Making	Koosha Khalvati, Saghar Mirbagheri, Seongmin A. Park, JeanClaude Dreher, Rajesh P. Rao		code	-1
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel	Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma		code	-1
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation	Colin Wei, Tengyu Ma		code	-1
A Benchmark for Interpretability Methods in Deep Neural Networks	Sara Hooker, Dumitru Erhan, PieterJan Kindermans, Been Kim		code	-1
Memory Efficient Adaptive Optimization	Rohan Anil, Vineet Gupta, Tomer Koren, Yoram Singer		code	-1
Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions	Negin Golrezaei, Adel Javanmard, Vahab S. Mirrokni		code	-1
Convergence-Rate-Matching Discretization of Accelerated Optimization Flows Through Opportunistic State-Triggered Control	Miguel Vaquero, Jorge Cortés		code	-1
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning	Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, ChoJui Hsieh		code	-1
Compositional generalization through meta sequence-to-sequence learning	Brenden M. Lake		code	-1
Bayesian Joint Estimation of Multiple Graphical Models	Lingrui Gan, Xinming Yang, Naveen N. Narisetty, Feng Liang		code	-1
Practical Two-Step Lookahead Bayesian Optimization	Jian Wu, Peter I. Frazier		code	-1
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models	Yunfei Teng, Wenbo Gao, Anna Choromanska, Donald Goldfarb, Adrian Weller		code	-1
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks	Hadi Salman, Greg Yang, Huan Zhang, ChoJui Hsieh, Pengchuan Zhang		code	-1
Neural Jump Stochastic Differential Equations	Junteng Jia, Austin R. Benson		code	-1
Learning metrics for persistence-based summaries and applications for graph classification	Qi Zhao, Yusu Wang		code	-1
On the Value of Target Data in Transfer Learning	Steve Hanneke, Samory Kpotufe		code	-1
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization	Adithya M. Devraj, Jianshu Chen		code	-1
On Robustness of Principal Component Regression	Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song		code	-1
Meta Learning with Relational Information for Short Sequences	Yujia Xie, Haoming Jiang, Feng Liu, Tuo Zhao, Hongyuan Zha		code	-1
Residual Flows for Invertible Generative Modeling	Tian Qi Chen, Jens Behrmann, David Duvenaud, JörnHenrik Jacobsen		code	-1
Multi-Agent Common Knowledge Reinforcement Learning	Christian Schröder de Witt, Jakob N. Foerster, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson		code	-1
Learning to Learn By Self-Critique	Antreas Antoniou, Amos J. Storkey		code	-1
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes	Greg Yang		code	-1
Neural Networks with Cheap Differential Operators	Tian Qi Chen, David Duvenaud		code	-1
Transductive Zero-Shot Learning with Visual Structure Constraint	Ziyu Wan, Dongdong Chen, Yan Li, Xingguang Yan, Junge Zhang, Yizhou Yu, Jing Liao		code	-1
Dying Experts: Efficient Algorithms with Optimal Regret Bounds	Hamid Shayestehmanesh, Sajjad Azami, Nishant A. Mehta		code	-1
Model Similarity Mitigates Test Set Overuse	Horia Mania, John Miller, Ludwig Schmidt, Moritz Hardt, Benjamin Recht		code	-1
A unified theory for the origin of grid cells through the lens of pattern formation	Ben Sorscher, Gabriel Mel, Surya Ganguli, Samuel A. Ocko		code	-1
On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons	Wenbo Ren, Jia Liu, Ness B. Shroff		code	-1
Hierarchical Decision Making by Generating and Following Natural Language Instructions	Hengyuan Hu, Denis Yarats, Qucheng Gong, Yuandong Tian, Mike Lewis		code	-1
SHE: A Fast and Accurate Deep Neural Network for Encrypted Data	Qian Lou, Lei Jiang		code	-1
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond	Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni		code	-1
A Game Theoretic Approach to Class-wise Selective Rationalization	Shiyu Chang, Yang Zhang, Mo Yu, Tommi S. Jaakkola		code	-1
Efficiently avoiding saddle points with zero order methods: No gradients required	EmmanouilVasileios VlatakisGkaragkounis, Lampros Flokas, Georgios Piliouras		code	-1
Metamers of neural networks reveal divergence from human perceptual systems	Jenelle Feather, Alex Durango, Ray Gonzalez, Josh H. McDermott		code	-1
Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization	Yujiao Shi, Liu Liu, Xin Yu, Hongdong Li		code	-1
Decentralized sketching of low rank matrices	Rakshith Sharma Srinivasa, Kiryung Lee, Marius Junge, Justin Romberg		code	-1
Average Case Column Subset Selection for Entrywise 퓁1-Norm Loss	Zhao Song, David P. Woodruff, Peilin Zhong		code	-1
Efficient Forward Architecture Search	Hanzhang Hu, John Langford, Rich Caruana, Saurajit Mukherjee, Eric Horvitz, Debadeepta Dey		code	-1
Unsupervised Meta-Learning for Few-Shot Image Classification	Siavash Khodadadeh, Ladislau Bölöni, Mubarak Shah		code	-1
Learning Mixtures of Plackett-Luce Models from Structured Partial Orders	Zhibing Zhao, Lirong Xia		code	-1
Certainty Equivalence is Efficient for Linear Quadratic Control	Horia Mania, Stephen Tu, Benjamin Recht		code	-1
Scalable Bayesian inference of dendritic voltage via spatiotemporal recurrent state space models	Ruoxi Sun, Scott W. Linderman, Ian Kinsella, Liam Paninski		code	-1
Logarithmic Regret for Online Control	Naman Agarwal, Elad Hazan, Karan Singh		code	-1
Elliptical Perturbations for Differential Privacy	Matthew Reimherr, Jordan Awan		code	-1
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks	Yaqin Zhou, Shangqing Liu, Jing Kai Siow, Xiaoning Du, Yang Liu		code	-1
KNG: The K-Norm Gradient Mechanism	Matthew Reimherr, Jordan Awan		code	-1
CXPlain: Causal Explanations for Model Interpretation under Uncertainty	Patrick Schwab, Walter Karlen		code	-1
Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning	Wenjie Shi, Shiji Song, Hui Wu, YaChu Hsu, Cheng Wu, Gao Huang		code	-1
STREETS: A Novel Camera Network Dataset for Traffic Flow	Corey Snyder, Minh Do		code	-1
Sequential Neural Processes	Gautam Singh, Jaesik Yoon, Youngsung Son, Sungjin Ahn		code	-1
Policy Continuation with Hindsight Inverse Dynamics	Hao Sun, Zhizhong Li, Xiaotong Liu, Bolei Zhou, Dahua Lin		code	-1
Learning to Self-Train for Semi-Supervised Few-Shot Classification	Xinzhe Li, Qianru Sun, Yaoyao Liu, Qin Zhou, Shibao Zheng, TatSeng Chua, Bernt Schiele		code	-1
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations	Sawyer Birnbaum, Volodymyr Kuleshov, S. Zayd Enam, Pang Wei Koh, Stefano Ermon		code	-1
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization	Krzysztof Choromanski, Aldo Pacchiano, Jack ParkerHolder, Yunhao Tang, Vikas Sindhwani		code	-1
On the Expressive Power of Deep Polynomial Neural Networks	Joe Kileel, Matthew Trager, Joan Bruna		code	-1
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation	Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris S. Papailiopoulos		code	-1
Can SGD Learn Recurrent Neural Networks with Provable Generalization?	Zeyuan AllenZhu, Yuanzhi Li		code	-1
Limits of Private Learning with Access to Public Data	Raef Bassily, Shay Moran, Noga Alon		code	-1
Discrete Object Generation with Reversible Inductive Construction	Ari Seff, Wenda Zhou, Farhan N. Damani, Abigail G. Doyle, Ryan P. Adams		code	-1
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models	Aditya Gangrade, Praveen Venkatesh, Bobak Nazer, Venkatesh Saligrama		code	-1
Keeping Your Distance: Solving Sparse Reward Tasks Using Self-Balancing Shaped Rewards	Alexander Trott, Stephan Zheng, Caiming Xiong, Richard Socher		code	-1
Superset Technique for Approximate Recovery in One-Bit Compressed Sensing	Larkin Flodin, Venkata Gandikota, Arya Mazumdar		code	-1
Bandits with Feedback Graphs and Switching Costs	Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri		code	-1
Functional Adversarial Attacks	Cassidy Laidlaw, Soheil Feizi		code	-1
Statistical-Computational Tradeoff in Single Index Models	Lingxiao Wang, Zhuoran Yang, Zhaoran Wang		code	-1
On Fenchel Mini-Max Learning	Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy V. Bobashev, Lawrence Carin		code	-1
MarginGAN: Adversarial Training in Semi-Supervised Learning	Jinhao Dong, Tong Lin		code	-1
Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games	EmmanouilVasileios VlatakisGkaragkounis, Lampros Flokas, Georgios Piliouras		code	-1
A unified variance-reduced accelerated gradient method for convex optimization	Guanghui Lan, Zhize Li, Yi Zhou		code	-1
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin	Ilias Diakonikolas, Daniel Kane, Pasin Manurangsi		code	-1
Same-Cluster Querying for Overlapping Clusters	Wasim Huleihel, Arya Mazumdar, Muriel Médard, Soumyabrata Pal		code	-1
Efficient Convex Relaxations for Streaming PCA	Raman Arora, Teodor Vanislavov Marinov		code	-1
Learning Robust Global Representations by Penalizing Local Predictive Power	Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing		code	-1
Unsupervised Curricula for Visual Meta-Reinforcement Learning	Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn		code	-1
Sample Complexity of Learning Mixture of Sparse Linear Regressions	Akshay Krishnamurthy, Arya Mazumdar, Andrew McGregor, Soumyabrata Pal		code	-1
Large Scale Adversarial Representation Learning	Jeff Donahue, Karen Simonyan		code	-1
G2SAT: Learning to Generate SAT Formulas	Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec		code	-1
Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy	Boyi Liu, Qi Cai, Zhuoran Yang, Zhaoran Wang		code	-1
Dimensionality reduction: theoretical perspective on practical measures	Yair Bartal, Nova Fandina, Ofer Neiman		code	-1
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback	Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Kenichi Kawarabayashi		code	-1
Multilabel reductions: what is my loss optimising?			code	-1
Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks	Yuan Cao, Quanquan Gu		code	-1
Deep Gamblers: Learning to Abstain with Portfolio Theory	Ziyin Liu, Zhikang Wang, Paul Pu Liang, Ruslan Salakhutdinov, LouisPhilippe Morency, Masahito Ueda		code	-1
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples	Tengyu Xu, Shaofeng Zou, Yingbin Liang		code	-1
Transfer Learning via Minimizing the Performance Gap Between Domains	Boyu Wang, Jorge A. Mendez, Mingbo Cai, Eric Eaton		code	-1
Splitting Steepest Descent for Growing Neural Architectures	Lemeng Wu, Dilin Wang, Qiang Liu		code	-1
Sequential Experimental Design for Transductive Linear Bandits	Tanner Fiez, Lalit Jain, Kevin G. Jamieson, Lillian J. Ratliff		code	-1
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence	Aditya Golatkar, Alessandro Achille, Stefano Soatto		code	-1
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering	Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Eric Price, Alistair Stewart		code	-1
Variational Graph Recurrent Neural Networks	Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian		code	-1
Semi-Implicit Graph Variational Auto-Encoders	Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna R. Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian		code	-1
Unsupervised Learning of Object Keypoints for Perception and Control	Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih		code	-1
A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation	Xueying Bai, Jian Guan, Hongning Wang		code	-1
Optimizing Generalized Rate Metrics with Three Players	Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta		code	-1
Consistency-based Semi-supervised Learning for Object detection	Jisoo Jeong, Seungeui Lee, Jeesoo Kim, Nojun Kwak		code	-1
Rates of Convergence for Large-scale Nearest Neighbor Classification	Xingye Qiao, Jiexin Duan, Guang Cheng		code	-1
An Embedding Framework for Consistent Polyhedral Surrogates	Jessica Finocchiaro, Rafael M. Frongillo, Bo Waggoner		code	-1
Cross-Modal Learning with Adversarial Samples	Chao Li, Shangqian Gao, Cheng Deng, De Xie, Wei Liu		code	-1
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes	Jun Yang, Shengyang Sun, Daniel M. Roy		code	-1
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks	Aya Abdelsalam Ismail, Mohamed K. Gunady, Luiz Pessoa, Héctor Corrada Bravo, Soheil Feizi		code	-1
Program Synthesis and Semantic Parsing with Learned Code Idioms	Eui Chul Richard Shin, Miltiadis Allamanis, Marc Brockschmidt, Alex Polozov		code	-1
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks	Yuan Cao, Quanquan Gu		code	-1
High-Dimensional Optimization in Adaptive Random Subspaces	Jonathan Lacotte, Mert Pilanci, Marco Pavone		code	-1
Random Projections with Asymmetric Quantization	Xiaoyun Li, Ping Li		code	-1
Superposition of many models into one	Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen		code	-1
Private Testing of Distributions via Sample Permutations	Maryam Aliakbarpour, Ilias Diakonikolas, Daniel Kane, Ronitt Rubinfeld		code	-1
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds	Rui Ray Zhang, Xingwu Liu, Yuyi Wang, Liwei Wang		code	-1
How to Initialize your Network? Robust Initialization for WeightNorm & ResNets	Devansh Arpit, Víctor Campos, Yoshua Bengio		code	-1
On Making Stochastic Classifiers Deterministic	Andrew Cotter, Maya R. Gupta, Harikrishna Narasimhan		code	-1
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection	Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo		code	-1
Improving Black-box Adversarial Attacks with a Transfer-based Prior	Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu		code	-1
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	Sitao Luan, Mingde Zhao, XiaoWen Chang, Doina Precup		code	-1
Statistical Model Aggregation via Parameter Matching	Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan H. Greenewald, Trong Nghia Hoang		code	-1
On the (In)fidelity and Sensitivity of Explanations	ChihKuan Yeh, ChengYu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar		code	-1
Exponential Family Estimation via Adversarial Dynamics Embedding	Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, Dale Schuurmans		code	-1
The Broad Optimality of Profile Maximum Likelihood	Yi Hao, Alon Orlitsky		code	-1
MintNet: Building Invertible Neural Networks with Masked Convolutions	Yang Song, Chenlin Meng, Stefano Ermon		code	-1
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates	Jeffrey Negrea, Mahdi Haghifam, Gintare Karolina Dziugaite, Ashish Khisti, Daniel M. Roy		code	-1
On Distributed Averaging for Stochastic k-PCA	Aditya Bhaskara, Maheshakya Wijewardena		code	-1
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation	Ke Wang, Hang Hua, Xiaojun Wan		code	-1
MaxGap Bandit: Adaptive Algorithms for Approximate Ranking	Sumeet Katariya, Ardhendu Tripathy, Robert D. Nowak		code	-1
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting	Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon		code	-1
Online Forecasting of Total-Variation-bounded Sequences	Dheeraj Baby, YuXiang Wang		code	-1
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization	Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Viveck R. Cadambe		code	-1
Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum	Shreyas Saxena, Oncel Tuzel, Dennis DeCoste		code	-1
Unified Sample-Optimal Property Estimation in Near-Linear Time	Yi Hao, Alon Orlitsky		code	-1
Region Mutual Information Loss for Semantic Segmentation	Shuai Zhao, Yang Wang, Zheng Yang, Deng Cai		code	-1
Learning Stable Deep Dynamics Models	J. Zico Kolter, Gaurav Manek		code	-1
Image Captioning: Transforming Objects into Words	Simao Herdade, Armin Kappeler, Kofi Boakye, Joao Soares		code	-1
Greedy Sampling for Approximate Clustering in the Presence of Outliers	Aditya Bhaskara, Sharvaree Vadgama, Hong Xu		code	-1
Adversarial Fisher Vectors for Unsupervised Representation Learning	Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind		code	-1
On Tractable Computation of Expected Predictions	Pasha Khosravi, YooJung Choi, Yitao Liang, Antonio Vergari, Guy Van den Broeck		code	-1
Levenshtein Transformer	Jiatao Gu, Changhan Wang, Junbo Zhao		code	-1
Unlabeled Data Improves Adversarial Robustness	Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, John C. Duchi, Percy Liang		code	-1
Machine Teaching of Active Sequential Learners	Tomi Peltola, Mustafa Mert Çelikok, Pedram Daee, Samuel Kaski		code	-1
Gaussian-Based Pooling for Convolutional Neural Networks	Takumi Kobayashi		code	-1
Meta Architecture Search	Albert E. Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai		code	-1
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation	Yukai Liu, Rose Yu, Stephan Zheng, Eric Zhan, Yisong Yue		code	-1
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks	Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun, Quanquan Gu		code	-1
Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test	Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu, Yu Li, Ling Shao		code	-1
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards	Anmol Kagrecha, Jayakrishnan Nair, Krishna P. Jagannathan		code	-1
Private Stochastic Convex Optimization with Optimal Rates	Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Guha Thakurta		code	-1
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers	Hadi Salman, Jerry Li, Ilya P. Razenshteyn, Pengchuan Zhang, Huan Zhang, Sébastien Bubeck, Greg Yang		code	-1
Demystifying Black-box Models with Symbolic Metamodels	Ahmed M. Alaa, Mihaela van der Schaar		code	-1
Neural Temporal-Difference Learning Converges to Global Optima	Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang		code	-1
Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces	Baoxiang Wang, Nidhi Hegde		code	-1
Attentive State-Space Modeling of Disease Progression	Ahmed M. Alaa, Mihaela van der Schaar		code	-1
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback	Ilai Bistritz, Zhengyuan Zhou, Xi Chen, Nicholas Bambos, Jose H. Blanchet		code	-1
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport	Arun Jambulapati, Aaron Sidford, Kevin Tian		code	-1
Faster Boosting with Smaller Memory	Julaiti Alafate, Yoav Freund		code	-1
Variance Reduction for Matrix Games	Yair Carmon, Yujia Jin, Aaron Sidford, Kevin Tian		code	-1
Learning Neural Networks with Adaptive Regularization	Han Zhao, YaoHung Hubert Tsai, Ruslan Salakhutdinov, Geoffrey J. Gordon		code	-1
Distributed estimation of the inverse Hessian by determinantal averaging	Michal Derezinski, Michael W. Mahoney		code	-1
Smoothing Structured Decomposable Circuits	Andy Shih, Guy Van den Broeck, Paul Beame, Antoine Amarilli		code	-1
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks	Mahyar Fazlyab, Alexander Robey, Hamed Hassani, Manfred Morari, George J. Pappas		code	-1
Provable Non-linear Inductive Matrix Completion	Kai Zhong, Zhao Song, Prateek Jain, Inderjit S. Dhillon		code	-1
Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback	Shuai Zheng, Ziyue Huang, James T. Kwok		code	-1
Sparse Variational Inference: Bayesian Coresets from Scratch	Trevor Campbell, Boyan Beronov		code	-1
Personalizing Many Decisions with High-Dimensional Covariates	Nima Hamidi, Mohsen Bayati, Kapil Gupta		code	-1
A Necessary and Sufficient Stability Notion for Adaptive Generalization	Moshe Shenfeld, Katrina Ligett		code	-1
Necessary and Sufficient Geometries for Gradient Methods	Daniel Levy, John C. Duchi		code	-1
Landmark Ordinal Embedding	Nikhil Ghosh, Yuxin Chen, Yisong Yue		code	-1
Identification of Conditional Causal Effects under Markov Equivalence	Amin Jaber, Jiji Zhang, Elias Bareinboim		code	-1
The Thermodynamic Variational Objective	Vaden Masrani, Tuan Anh Le, Frank Wood		code	-1
Global Guarantees for Blind Demodulation with Generative Priors	Paul Hand, Babhru Joshi		code	-1
Exact sampling of determinantal point processes with sublinear time preprocessing	Michal Derezinski, Daniele Calandriello, Michal Valko		code	-1
Geometry-Aware Neural Rendering	Joshua Tobin, Wojciech Zaremba, Pieter Abbeel		code	-1
Variational Temporal Abstraction	Taesup Kim, Sungjin Ahn, Yoshua Bengio		code	-1
Subquadratic High-Dimensional Hierarchical Clustering	Amir Abboud, Vincent CohenAddad, Hussein Houdrouge		code	-1
Learning Auctions with Robust Incentive Guarantees	Jacob D. Abernethy, Rachel Cummings, Bhuvesh Kumar, Sam Taggart, Jamie Morgenstern		code	-1
Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games	Kaiqing Zhang, Zhuoran Yang, Tamer Basar		code	-1
Uniform convergence may be unable to explain generalization in deep learning	Vaishnavh Nagarajan, J. Zico Kolter		code	-1
A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions	Mejbah Alam, Justin Gottschlich, Nesime Tatbul, Javier S. Turek, Tim Mattson, Abdullah Muzahid		code	-1
DTWNet: a Dynamic Time Warping Network	Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang, Sanguthevar Rajasekaran		code	-1
Structured Graph Learning Via Laplacian Spectral Constraints	Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar		code	-1
Thresholding Bandit with Optimal Aggregate Regret	Chao Tao, Saúl A. Blanco, Jian Peng, Yuan Zhou		code	-1
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks	Yuanzhi Li, Colin Wei, Tengyu Ma		code	-1
Rethinking Kernel Methods for Node Representation Learning on Graphs	Yu Tian, Long Zhao, Xi Peng, Dimitris N. Metaxas		code	-1
Causal Confusion in Imitation Learning	Pim de Haan, Dinesh Jayaraman, Sergey Levine		code	-1
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection	Pan Li, I (Eli) Chien, Olgica Milenkovic		code	-1
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data	Amanda Gentzel, Dan Garant, David D. Jensen		code	-1
Dimension-Free Bounds for Low-Precision Training	Zheng Li, Christopher De Sa		code	-1
Concentration of risk measures: A Wasserstein distance approach	Sanjay P. Bhat, Prashanth L. A.		code	-1
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables	Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon		code	-1
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction	Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine		code	-1
Bayesian Optimization with Unknown Search Space	Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung TranThe, Svetha Venkatesh		code	-1
On the Downstream Performance of Compressed Word Embeddings	Avner May, Jian Zhang, Tri Dao, Christopher Ré		code	-1
Multivariate Distributionally Robust Convex Regression under Absolute Error Loss	Jose H. Blanchet, Peter W. Glynn, Jun Yan, Zhengqing Zhou		code	-1
Neural Relational Inference with Fast Modular Meta-learning	Ferran Alet, Erica Weng, Tomás LozanoPérez, Leslie Pack Kaelbling		code	-1
Gradient based sample selection for online continual learning	Rahaf Aljundi, Min Lin, Baptiste Goujaud, Yoshua Bengio		code	-1
Attribution-Based Confidence Metric For Deep Neural Networks	Susmit Jha, Sunny Raj, Steven Lawrence Fernandes, Sumit Kumar Jha, Somesh Jha, Brian Jalaian, Gunjan Verma, Ananthram Swami		code	-1
Theoretical evidence for adversarial robustness through randomization	Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric GouyPailler, Jamal Atif		code	-1
Online Continual Learning with Maximal Interfered Retrieval	Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, Lucas PageCaccia		code	-1
Neural Attribution for Semantic Bug-Localization in Student Programs	Rahul Gupta, Aditya Kanade, Shirish K. Shevade		code	-1
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates	Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu		code	-1
SPoC: Search-based Pseudocode to Code	Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, Percy Liang		code	-1
Generative Modeling by Estimating Gradients of the Data Distribution	Yang Song, Stefano Ermon		code	-1
Adversarial Music: Real world Audio Adversary against Wake-word Detection System	Juncheng Li, Shuhui Qu, Xinjian Li, Joseph Szurley, J. Zico Kolter, Florian Metze		code	-1
Prediction of Spatial Point Processes: Regularized Method with Out-of-Sample Guarantees	Muhammad Osama, Dave Zachariah, Peter Stoica		code	-1
Debiased Bayesian inference for average treatment effects	Kolyan Ray, Botond Szabó		code	-1
Margin-Based Generalization Lower Bounds for Boosted Classifiers	Allan Grønlund, Lior Kamma, Kasper Green Larsen, Alexander Mathiasen, Jelani Nelson		code	-1
Connections Between Mirror Descent, Thompson Sampling and the Information Ratio	Julian Zimmert, Tor Lattimore		code	-1
Graph Transformer Networks	Seongjun Yun, Minbyul Jeong, Raehyun Kim, Jaewoo Kang, Hyunwoo J. Kim		code	-1
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder	Ji Feng, QiZhi Cai, ZhiHua Zhou		code	-1
The Impact of Regularization on High-dimensional Logistic Regression	Fariborz Salehi, Ehsan Abbasi, Babak Hassibi		code	-1
Adaptive Density Estimation for Generative Models	Thomas Lucas, Konstantin Shmelkov, Karteek Alahari, Cordelia Schmid, Jakob Verbeek		code	-1
Fast and Provable ADMM for Learning with Generative Priors	Fabian Latorre Gómez, Armin Eftekhari, Volkan Cevher		code	-1
Weighted Linear Bandits for Non-Stationary Environments	Yoan Russac, Claire Vernade, Olivier Cappé		code	-1
Improved Regret Bounds for Bandit Combinatorial Optimization	Shinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Kenichi Kawarabayashi		code	-1
Pareto Multi-Task Learning	Xi Lin, HuiLing Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong		code	-1
SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits	Etienne Boursier, Vianney Perchet		code	-1
Novel positional encodings to enable tree-based transformers	Vighnesh Leonardo Shiv, Chris Quirk		code	-1
A Domain Agnostic Measure for Monitoring and Evaluating GANs	Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian Goodfellow, Thomas Hofmann, Andreas Krause		code	-1
Submodular Function Minimization with Noisy Evaluation Oracle	Shinji Ito		code	-1
Counting the Optimal Solutions in Graphical Models	Radu Marinescu, Rina Dechter		code	-1
Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach	Shuyue Hu, Chinwing Leung, Hofung Leung		code	-1
Deep Multimodal Multilinear Fusion with High-order Polynomial Pooling	Ming Hou, Jiajia Tang, Jianhai Zhang, Wanzeng Kong, Qibin Zhao		code	-1
Bootstrapping Upper Confidence Bound	Botao Hao, Yasin AbbasiYadkori, Zheng Wen, Guang Cheng		code	-1
Integer Discrete Flows and Lossless Compression	Emiel Hoogeboom, Jorn W. T. Peters, Rianne van den Berg, Max Welling		code	-1
Structured Prediction with Projection Oracles	Mathieu Blondel		code	-1
A Primal Dual Formulation For Deep Learning With Constraints	Yatin Nandwani, Abhishek Pathak, Mausam, Parag Singla		code	-1
Screening Sinkhorn Algorithm for Regularized Optimal Transport	Mokhtar Z. Alaya, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy		code	-1
PAC-Bayes Un-Expected Bernstein Inequality	Zakaria Mhammedi, Peter Grünwald, Benjamin Guedj		code	-1
Are Labels Required for Improving Adversarial Robustness?	JeanBaptiste Alayrac, Jonathan Uesato, PoSen Huang, Alhussein Fawzi, Robert Stanforth, Pushmeet Kohli		code	-1
Tight Regret Bounds for Model-Based Reinforcement Learning with Greedy Policies	Yonathan Efroni, Nadav Merlis, Mohammad Ghavamzadeh, Shie Mannor		code	-1
Multi-objective Bayesian optimisation with preferences over objectives	Majid Abdolshah, Alistair Shilton, Santu Rana, Sunil Gupta, Svetha Venkatesh		code	-1
Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging	Pooria Joulani, András György, Csaba Szepesvári		code	-1
Calibration tests in multi-class classification: A unifying framework	David Widmann, Fredrik Lindsten, Dave Zachariah		code	-1
Classification Accuracy Score for Conditional Generative Models	Suman V. Ravuri, Oriol Vinyals		code	-1
Theoretical Analysis of Adversarial Learning: A Minimax Approach	Zhuozhuo Tu, Jingwei Zhang, Dacheng Tao		code	-1
Multiagent Evaluation under Incomplete Information	Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos		code	-1
Tree-Sliced Variants of Wasserstein Distances	Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi		code	-1
Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration	Meelis Kull, Miquel PerellóNieto, Markus Kängsepp, Telmo de Menezes e Silva Filho, Hao Song, Peter A. Flach		code	-1
Comparing distributions: 퓁1 geometry improves kernel two-sample testing	Meyer Scetbon, Gaël Varoquaux		code	-1
Robustness Verification of Tree-based Models	Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, ChoJui Hsieh		code	-1
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents	Alexander Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo Jimenez Rezende		code	-1
Fast and Accurate Stochastic Gradient Estimation	Beidi Chen, Yingchen Xu, Anshumali Shrivastava		code	-1
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning	Igor Colin, Ludovic Dos Santos, Kevin Scaman		code	-1
Root Mean Square Layer Normalization	Biao Zhang, Rico Sennrich		code	-1
Universality in Learning from Linear Measurements	Ehsan Abbasi, Fariborz Salehi, Babak Hassibi		code	-1
Planning in entropy-regularized Markov decision processes and games	JeanBastien Grill, Omar Darwiche Domingues, Pierre Ménard, Rémi Munos, Michal Valko		code	-1
Exponentially convergent stochastic k-PCA without variance reduction	Cheng Tang		code	-1
R2D2: Reliable and Repeatable Detector and Descriptor	Jérôme Revaud, César Roberto de Souza, Martin Humenberger, Philippe Weinzaepfel		code	-1
Selective Sampling-based Scalable Sparse Subspace Clustering	Shin Matsushima, Maria Brbic		code	-1
A General Framework for Symmetric Property Estimation	Moses Charikar, Kirankumar Shiragur, Aaron Sidford		code	-1
Structured Variational Inference in Continuous Cox Process Models	Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps		code	-1
Generalization of Reinforcement Learners with Working and Episodic Memory	Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z. Leibo, Charles Blundell		code	-1
Distribution Learning of a Random Spatial Field with a Location-Unaware Mobile Sensor	Meera Pai, Animesh Kumar		code	-1
Hindsight Credit Assignment	Anna Harutyunyan, Will Dabney, Thomas Mesnard, Mohammad Gheshlaghi Azar, Bilal Piot, Nicolas Heess, Hado van Hasselt, Gregory Wayne, Satinder Singh, Doina Precup, Rémi Munos		code	-1
Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets	Daniel Kumor, Bryant Chen, Elias Bareinboim		code	-1
Kernelized Bayesian Softmax for Text Generation	Ning Miao, Hao Zhou, Chengqi Zhao, Wenxian Shi, Lei Li		code	-1
When to Trust Your Model: Model-Based Policy Optimization	Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine		code	-1
Correlation Clustering with Adaptive Similarity Queries	Marco Bressan, Nicolò CesaBianchi, Andrea Paudice, Fabio Vitale		code	-1
Control What You Can: Intrinsically Motivated Task-Planning Agent	Sebastian Blaes, Marin Vlastelica Pogancic, JiaJie Zhu, Georg Martius		code	-1
Selecting causal brain features with a single conditional independence test per feature	AtalantiAnastasia Mastakouri, Bernhard Schölkopf, Dominik Janzing		code	-1
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders	Emile Mathieu, Charline Le Lan, Chris J. Maddison, Ryota Tomioka, Yee Whye Teh		code	-1
A Generic Acceleration Framework for Stochastic Composite Optimization	Andrei Kulunchakov, Julien Mairal		code	-1
Beating SGD Saturation with Tail-Averaging and Minibatching	Nicole Mücke, Gergely Neu, Lorenzo Rosasco		code	-1
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond	Arindam Banerjee, Qilong Gu, Vidyashankar Sivakumar, Zhiwei Steven Wu		code	-1
Continuous-time Models for Stochastic Optimization Algorithms	Antonio Orvieto, Aurélien Lucchi		code	-1
Curriculum-guided Hindsight Experience Replay	Meng Fang, Tianyi Zhou, Yali Du, Lei Han, Zhengyou Zhang		code	-1
Implicit Semantic Data Augmentation for Deep Networks	Yulin Wang, Xuran Pan, Shiji Song, Hong Zhang, Gao Huang, Cheng Wu		code	-1
MetaInit: Initializing learning by learning to initialize	Yann N. Dauphin, Samuel S. Schoenholz		code	-1
Scalable Deep Generative Relational Model with High-Order Node Dependence	Xuhui Fan, Bin Li, Caoyuan Li, Scott A. Sisson, Ling Chen		code	-1
Random Path Selection for Continual Learning	Jathushan Rajasegaran, Munawar Hayat, Salman H. Khan, Fahad Shahbaz Khan, Ling Shao		code	-1
Efficient Algorithms for Smooth Minimax Optimization	Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh		code	-1
Shadowing Properties of Optimization Algorithms	Antonio Orvieto, Aurélien Lucchi		code	-1
Causal Regularization	Dominik Janzing		code	-1
Learning Hawkes Processes from a handful of events	Farnood Salehi, William Trouleau, Matthias Grossglauser, Patrick Thiran		code	-1
Unsupervised Object Segmentation by Redrawing	Mickaël Chen, Thierry Artières, Ludovic Denoyer		code	-1
Regret Bounds for Learning State Representations in Reinforcement Learning	Ronald Ortner, Matteo Pirotta, Alessandro Lazaric, Ronan Fruit, OdalricAmbrym Maillard		code	-1
Band-Limited Gaussian Processes: The Sinc Kernel	Felipe A. Tobar		code	-1
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification	Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil		code	-1
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning	Valerio Perrone, Huibin Shen		code	-1
Streaming Bayesian Inference for Crowdsourced Classification	Edoardo Manino, Long TranThanh, Nicholas R. Jennings		code	-1
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation	Ruibo Tu, Kun Zhang, Bo C. Bertilson, Hedvig Kjellström, Cheng Zhang		code	-1
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs	Jonas Kubilius, Martin Schrimpf, Ha Hong, Najib J. Majaj, Rishi Rajalingham, Elias B. Issa, Kohitij Kar, Pouya Bashivan, Jonathan PrescottRoy, Kailyn Schmidt, Aran Nayebi, Daniel Bear, Daniel L. K. Yamins, James J. DiCarlo		code	-1
k-Means Clustering of Lines for Big Data	Yair Marom, Dan Feldman		code	-1
Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves	Stefan Meintrup, Alexander Munteanu, Dennis Rohde		code	-1
Recurrent Space-time Graph Neural Networks	Andrei Liviu Nicolicioiu, Iulia Duta, Marius Leordeanu		code	-1
Uncertainty on Asynchronous Time Event Prediction	Bertrand Charpentier, Marin Bilos, Stephan Günnemann		code	-1
Accurate, reliable and fast robustness evaluation	Wieland Brendel, Jonas Rauber, Matthias Kümmerer, Ivan Ustyuzhaninov, Matthias Bethge		code	-1
Sparse High-Dimensional Isotonic Regression	David Gamarnik, Julia Gaudio		code	-1
Triad Constraints for Learning Causal Structure of Latent Variables	Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang		code	-1
On the Inductive Bias of Neural Tangent Kernels	Alberto Bietti, Julien Mairal		code	-1
Cross-Domain Transferability of Adversarial Perturbations	Muzammal Naseer, Salman H. Khan, Muhammad Haris Khan, Fahad Shahbaz Khan, Fatih Porikli		code	-1
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices	Don Kurian Dennis, Durmus Alp Emre Acar, Vikram Mandikal, Vinu Sankar Sadasivan, Venkatesh Saligrama, Harsha Vardhan Simhadri, Prateek Jain		code	-1
Kernel quadrature with DPPs	Ayoub Belhadji, Rémi Bardenet, Pierre Chainais		code	-1
REM: From Structural Entropy to Community Structure Deception	Yiwei Liu, Jiamou Liu, Zijian Zhang, Liehuang Zhu, Angsheng Li		code	-1
Sim2real transfer learning for 3D human pose estimation: motion to the rescue	Carl Doersch, Andrew Zisserman		code	-1
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space	Jonathan Sauder, Bjarne Sievers		code	-1
Piecewise Strong Convexity of Neural Networks	Tristan Milne		code	-1
Minimum Stein Discrepancy Estimators	Alessandro Barp, FrançoisXavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey		code	-1
Fast and Furious Learning in Zero-Sum Games: Vanishing Regret with Non-Vanishing Step Sizes	James P. Bailey, Georgios Piliouras		code	-1
Generalization Bounds for Neural Networks via Approximate Description Length	Amit Daniely, Elad Granot		code	-1
Provably robust boosted decision stumps and trees against adversarial attacks	Maksym Andriushchenko, Matthias Hein		code	-1
Convergence of Adversarial Training in Overparametrized Neural Networks	Ruiqi Gao, Tianle Cai, Haochuan Li, ChoJui Hsieh, Liwei Wang, Jason D. Lee		code	-1
A Composable Specification Language for Reinforcement Learning Tasks	Kishor Jothimurugan, Rajeev Alur, Osbert Bastani		code	-1
The Option Keyboard: Combining Skills in Reinforcement Learning	André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup		code	-1
Unified Language Model Pre-training for Natural Language Understanding and Generation	Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, HsiaoWuen Hon		code	-1
Learning to Correlate in Multi-Player General-Sum Sequential Games	Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti		code	-1
Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match	Amin Karbasi, Hamed Hassani, Aryan Mokhtari, Zebang Shen		code	-1
Generative Well-intentioned Networks	Justin Cosentino, Jun Zhu		code	-1
Online-Within-Online Meta-Learning	Giulia Denevi, Dimitris Stamos, Carlo Ciliberto, Massimiliano Pontil		code	-1
Learning step sizes for unfolded sparse coding	Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort		code	-1
Biases for Emergent Communication in Multi-agent Reinforcement Learning	Tom Eccles, Yoram Bachrach, Guy Lever, Angeliki Lazaridou, Thore Graepel		code	-1
Episodic Memory in Lifelong Language Learning	Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama		code	-1
A Simple Baseline for Bayesian Uncertainty in Deep Learning	Wesley J. Maddox, Pavel Izmailov, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson		code	-1
Communication-efficient Distributed SGD with Sketching	Nikita Ivkin, Daniel Rothchild, Enayat Ullah, Vladimir Braverman, Ion Stoica, Raman Arora		code	-1
Modeling Conceptual Understanding in Image Reference Games	Rodolfo Corona, Stephan Alaniz, Zeynep Akata		code	-1
Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights	Maria Jahja, David C. Farrow, Roni Rosenfeld, Ryan J. Tibshirani		code	-1
Near Neighbor: Who is the Fairest of Them All?	Sariel HarPeled, Sepideh Mahabadi		code	-1
Outlier-robust estimation of a sparse linear model using \ell_1-penalized Huber's M-estimator	Arnak S. Dalalyan, Philip Thompson		code	-1
Learning nonlinear level sets for dimensionality reduction in function approximation	Guannan Zhang, Jiaxin Zhang, Jacob D. Hinkle		code	-1
Assessing Social and Intersectional Biases in Contextualized Word Representations	Yi Chern Tan, L. Elisa Celis		code	-1
Online Convex Matrix Factorization with Representative Regions	Jianhao Peng, Olgica Milenkovic, Abhishek Agarwal		code	-1
Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game	NgocTrung Tran, VietHung Tran, NgocBao Nguyen, Linxiao Yang, NgaiMan Cheung		code	-1
Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products	Tharun Medini, Qixuan Huang, Yiqiu Wang, Vijai Mohan, Anshumali Shrivastava		code	-1
The continuous Bernoulli: fixing a pervasive error in variational autoencoders	Gabriel LoaizaGanem, John P. Cunningham		code	-1
Privacy Amplification by Mixing and Diffusion Mechanisms	Borja Balle, Gilles Barthe, Marco Gaboardi, Joseph Geumlek		code	-1
Variance Reduction in Bipartite Experiments through Correlation Clustering	Jean PougetAbadie, Kevin Aydin, Warren Schudy, Kay Brodersen, Vahab S. Mirrokni		code	-1
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning	Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat		code	-1
Metalearned Neural Memory	Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler		code	-1
Learning Multiple Markov Chains via Adaptive Allocation	Mohammad Sadegh Talebi, OdalricAmbrym Maillard		code	-1
Diffusion Improves Graph Learning	Johannes Klicpera, Stefan Weißenberger, Stephan Günnemann		code	-1
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data	Gabriel LoaizaGanem, Sean Perkins, Karen Schroeder, Mark M. Churchland, John P. Cunningham		code	-1
Variational Bayes under Model Misspecification	Yixin Wang, David M. Blei		code	-1
Global Convergence of Gradient Descent for Deep Linear Residual Networks	Lei Wu, Qingcan Wang, Chao Ma		code	-1
On Differentially Private Graph Sparsification and Applications	Raman Arora, Jalaj Upadhyay		code	-1
Manifold denoising by Nonlinear Robust Principal Component Analysis	He Lyu, Ningyu Sha, Shuyang Qin, Ming Yan, Yuying Xie, Rongrong Wang		code	-1
Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes	Junzhe Zhang, Elias Bareinboim		code	-1
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks	Çagatay Yildiz, Markus Heinonen, Harri Lähdesmäki		code	-1
Optimal Sampling and Clustering in the Stochastic Block Model	SeYoung Yun, Alexandre Proutière		code	-1
Recurrent Kernel Networks	Dexiong Chen, Laurent Jacob, Julien Mairal		code	-1
Cold Case: The Lost MNIST Digits	Chhavi Yadav, Léon Bottou		code	-1
Hierarchical Optimal Transport for Multimodal Distribution Alignment	John Lee, Max Dabagia, Eva L. Dyer, Christopher Rozell		code	-1
Exploration via Hindsight Goal Generation	Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng		code	-1
Shaping Belief States with Generative Environment Models for RL	Karol Gregor, Danilo Jimenez Rezende, Frederic Besse, Yan Wu, Hamza Merzic, Aäron van den Oord		code	-1
Globally Optimal Learning for Structured Elliptical Losses	Yoav Wald, Nofar Noy, Gal Elidan, Ami Wiesel		code	-1
Object landmark discovery through unsupervised adaptation	Enrique Sanchez, Georgios Tzimiropoulos		code	-1
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering	Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour		code	-1
Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks	Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum		code	-1
Accelerating Rescaled Gradient Descent: Fast Optimization of Smooth Functions	Ashia C. Wilson, Lester Mackey, Andre Wibisono		code	-1
RUDDER: Return Decomposition for Delayed Rewards	Jose A. ArjonaMedina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter		code	-1
Graph Normalizing Flows	Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky		code	-1
Explanations can be manipulated and geometry is to blame	AnnKathrin Dombrowski, Maximilian Alber, Christopher J. Anders, Marcel Ackermann, KlausRobert Müller, Pan Kessel		code	-1
Communication trade-offs for Local-SGD with large step size	Aymeric Dieuleveut, Kumar Kshitij Patel		code	-1
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics	Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie		code	-1
No-Regret Learning in Unknown Games with Correlated Payoffs	Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause		code	-1
Alleviating Label Switching with Optimal Transport	Pierre Monteiller, Sebastian Claici, Edward Chien, Farzaneh Mirzazadeh, Justin M. Solomon, Mikhail Yurochkin		code	-1
Paraphrase Generation with Latent Bag of Words	Yao Fu, Yansong Feng, John P. Cunningham		code	-1
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors	Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin		code	-1
Compacting, Picking and Growing for Unforgetting Continual Learning	Steven C. Y. Hung, ChengHao Tu, ChengEn Wu, ChienHung Chen, YiMing Chan, ChuSong Chen		code	-1
Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems	Asma Ghandeharioun, Judy Hanwen Shen, Natasha Jaques, Craig Ferguson, Noah Jones, Àgata Lapedriza, Rosalind W. Picard		code	-1
A New Distribution on the Simplex with Auto-Encoding Applications	Andrew Stirn, Tony Jebara, David A. Knowles		code	-1
AutoPrune: Automatic Network Pruning by Regularizing Auxiliary Parameters	Xia Xiao, Zigeng Wang, Sanguthevar Rajasekaran		code	-1
A neurally plausible model learns successor representations in partially observable environments	Eszter Vértes, Maneesh Sahani		code	-1
Learning about an exponential amount of conditional distributions	Mohamed Ishmael Belghazi, Maxime Oquab, David LopezPaz		code	-1
Towards modular and programmable architecture search	Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon, Darshan Patil, Nghia Le, Daniel Ferreira		code	-1
Towards Hardware-Aware Tractable Learning of Probabilistic Models	Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck		code	-1
On Robustness to Adversarial Examples and Polynomial Optimization	Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan		code	-1
Rand-NSG: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node	Suhas Jayaram Subramanya, Fnu Devvrit, Harsha Vardhan Simhadri, Ravishankar Krishnaswamy, Rohan Kadekodi		code	-1
A Solvable High-Dimensional Model of GAN	Chuang Wang, Hong Hu, Yue M. Lu		code	-1
Using Embeddings to Correct for Unobserved Confounding in Networks	Victor Veitch, Yixin Wang, David M. Blei		code	-1
MonoForest framework for tree ensemble analysis	Igor Kuralenok, Vasilii Ershov, Igor Labutin		code	-1
Bayesian Optimization under Heavy-tailed Payoffs	Sayak Ray Chowdhury, Aditya Gopalan		code	-1
Combining Generative and Discriminative Models for Hybrid Inference	Victor Garcia Satorras, Max Welling, Zeynep Akata		code	-1
A Graph Theoretic Additive Approximation of Optimal Transport	Nathaniel Lahn, Deepika Mulchandani, Sharath Raghvendra		code	-1
Adversarial Robustness through Local Linearization	Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli		code	-1
Sampled Softmax with Random Fourier Features	Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar		code	-1
Semi-flat minima and saddle points by embedding neural networks to overparameterization	Kenji Fukumizu, Shoichiro Yamaguchi, Yohichi Mototake, Mirai Tanaka		code	-1
Learning Fairness in Multi-Agent Systems	Jiechuan Jiang, Zongqing Lu		code	-1
Primal-Dual Block Generalized Frank-Wolfe	Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis		code	-1
GOT: An Optimal Transport framework for Graph comparison	Hermina Petric Maretic, Mireille El Gheche, Giovanni Chierchia, Pascal Frossard		code	-1
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks	Sunil Thulasidasan, Gopinath Chennupati, Jeff A. Bilmes, Tanmoy Bhattacharya, Sarah Michalak		code	-1
Complexity of Highly Parallel Non-Smooth Convex Optimization	Sébastien Bubeck, Qijia Jiang, Yin Tat Lee, Yuanzhi Li, Aaron Sidford		code	-1
Inverting Deep Generative models, One layer at a time	Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis		code	-1
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization	Viet Anh Nguyen, Soroosh ShafieezadehAbadeh, ManChung Yue, Daniel Kuhn, Wolfram Wiesemann		code	-1
The Implicit Metropolis-Hastings Algorithm	Kirill Neklyudov, Evgenii Egorov, Dmitry P. Vetrov		code	-1
An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints	Mehmet Fatih Sahin, Armin Eftekhari, Ahmet Alacaoglu, Fabian Latorre Gómez, Volkan Cevher		code	-1
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck	Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann		code	-1
Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift	Jasper Snoek, Yaniv Ovadia, Emily Fertig, Balaji Lakshminarayanan, Sebastian Nowozin, D. Sculley, Joshua V. Dillon, Jie Ren, Zachary Nado		code	-1
Accurate Layerwise Interpretable Competence Estimation	Vickram Rajendran, William LeVine		code	-1
A New Perspective on Pool-Based Active Classification and False-Discovery Control	Lalit Jain, Kevin G. Jamieson		code	-1
Defending Neural Backdoors via Generative Distribution Modeling	Ximing Qiao, Yukun Yang, Hai Li		code	-1
Are Sixteen Heads Really Better than One?	Paul Michel, Omer Levy, Graham Neubig		code	-1
Multi-resolution Multi-task Gaussian Processes	Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami		code	-1
Variational Bayesian Optimal Experimental Design	Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah D. Goodman		code	-1
Universal Approximation of Input-Output Maps by Temporal Convolutional Nets	Joshua Hanson, Maxim Raginsky		code	-1
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes	Matt Jordan, Justin Lewis, Alexandros G. Dimakis		code	-1
Reinforcement Learning with Convex Constraints	Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire		code	-1
User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning	Dirk van der Hoeven		code	-1
Stochastic Bandits with Context Distributions	Johannes Kirschner, Andreas Krause		code	-1
Inducing brain-relevant bias in natural language processing models	Dan Schwartz, Mariya Toneva, Leila Wehbe		code	-1
Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning	Harm van Seijen, Mehdi Fatemi, Arash Tavakoli		code	-1
Recovering Bandits	Ciara PikeBurke, Steffen Grünewälder		code	-1
Computing Linear Restrictions of Neural Networks	Matthew Sotoudeh, Aditya V. Thakur		code	-1
Learning Positive Functions with Pseudo Mirror Descent	Yingxiang Yang, Haoxiang Wang, Negar Kiyavash, Niao He		code	-1
Correlation Priors for Reinforcement Learning	Bastian Alt, Adrian Sosic, Heinz Koeppl		code	-1
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression	Deeksha Adil, Richard Peng, Sushant Sachdeva		code	-1
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit	Yanis Bahroun, Dmitri B. Chklovskii, Anirvan M. Sengupta		code	-1
Differentially Private Covariance Estimation	Kareem Amin, Travis Dick, Alex Kulesza, Andres Muñoz Medina, Sergei Vassilvitskii		code	-1
Outlier Detection and Robust PCA Using a Convex Measure of Innovation	Mostafa Rahmani, Ping Li		code	-1
Integrating Markov processes with structural causal modeling enables counterfactual inference in complex systems	Robert Osazuwa Ness, Kaushal Paneri, Olga Vitek		code	-1
Are Disentangled Representations Helpful for Abstract Visual Reasoning?	Sjoerd van Steenkiste, Francesco Locatello, Jürgen Schmidhuber, Olivier Bachem		code	-1
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization	Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi		code	-1
Stochastic Frank-Wolfe for Composite Convex Minimization	Francesco Locatello, Alp Yurtsever, Olivier Fercoq, Volkan Cevher		code	-1
Constraint-based Causal Structure Learning with Consistent Separating Sets	Honghao Li, Vincent Cabeli, Nadir Sella, Hervé Isambert		code	-1
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis	David G. Clark, Jesse Livezey, Kristofer E. Bouchard		code	-1
Sample Efficient Active Learning of Causal Trees	Kristjan H. Greenewald, Dmitriy Katz, Karthikeyan Shanmugam, Sara Magliacane, Murat Kocaoglu, Enric Boix Adserà, Guy Bresler		code	-1
Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection	Junran Peng, Ming Sun, Zhaoxiang Zhang, Tieniu Tan, Junjie Yan		code	-1
Robust Attribution Regularization	Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha		code	-1
Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization	Miika Aittala, Prafull Sharma, Lukas Murmann, Adam B. Yedidia, Gregory W. Wornell, Bill Freeman, Frédo Durand		code	-1
When to use parametric models in reinforcement learning?	Hado van Hasselt, Matteo Hessel, John Aslanides		code	-1
General E(2)-Equivariant Steerable CNNs	Maurice Weiler, Gabriele Cesa		code	-1
Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions	Murat Kocaoglu, Amin Jaber, Karthikeyan Shanmugam, Elias Bareinboim		code	-1
Structure Learning with Side Information: Sample Complexity	Saurabh Sihag, Ali Tajer		code	-1
Untangling in Invariant Speech Recognition	Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz H. Elibol, Hanlin Tang, Josh H. McDermott, SueYeon Chung		code	-1
Flexible information routing in neural populations through stochastic comodulation	Caroline Haimerl, Cristina Savin, Eero P. Simoncelli		code	-1
Generalization Bounds in the Predict-then-Optimize Framework	Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari		code	-1
Categorized Bandits	Matthieu Jedor, Vianney Perchet, Jonathan Louëdec		code	-1
Worst-Case Regret Bounds for Exploration via Randomized Value Functions	Daniel Russo		code	-1
Efficient characterization of electrically evoked responses for neural interfaces	Nishal P. Shah, Sasidhar Madugula, Pawel Hottowy, Alexander Sher, Alan M. Litke, Liam Paninski, E. J. Chichilnisky		code	-1
Differentially Private Distributed Data Summarization under Covariate Shift	Kanthi K. Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu, Ashish Jagmohan, Roman Vaculín		code	-1
Hamiltonian descent for composite objectives	Brendan O'Donoghue, Chris J. Maddison		code	-1
Implicit Regularization of Accelerated Methods in Hilbert Spaces	Nicolò Pagliana, Lorenzo Rosasco		code	-1
Non-Asymptotic Pure Exploration by Solving Games	Rémy Degenne, Wouter M. Koolen, Pierre Ménard		code	-1
Implicit Posterior Variational Inference for Deep Gaussian Processes	Haibin Yu, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet, Zhongxiang Dai		code	-1
Deep Multi-State Dynamic Recurrent Neural Networks Operating on Wavelet Based Neural Features for Robust Brain Machine Interfaces	Benyamin Allahgholizadeh Haghi, Spencer S. Kellis, Sahil Shah, Maitreyi Ashok, Luke Bashford, Daniel Kramer, Brian C. Lee, Charles Liu, Richard A. Andersen, Azita Emami		code	-1
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback	Arun Verma, Manjesh Kumar Hanawal, Arun Rajkumar, Raman Sankaran		code	-1
Cormorant: Covariant Molecular Neural Networks	Brandon M. Anderson, TruongSon Hy, Risi Kondor		code	-1
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness	Andrey Malinin, Mark J. F. Gales		code	-1
Reflection Separation using a Pair of Unpolarized and Polarized Images	Youwei Lyu, Zhaopeng Cui, Si Li, Marc Pollefeys, Boxin Shi		code	-1
Policy Poisoning in Batch Reinforcement Learning and Control	Yuzhe Ma, Xuezhou Zhang, Wen Sun, Jerry Zhu		code	-1
Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees	Alix Lhéritier, Frédéric Cazals		code	-1
Pure Exploration with Multiple Correct Answers	Rémy Degenne, Wouter M. Koolen		code	-1
Explaining Landscape Connectivity of Low-cost Solutions for Multilayer Nets	Rohith Kuditipudi, Xiang Wang, Holden Lee, Yi Zhang, Zhiyuan Li, Wei Hu, Rong Ge, Sanjeev Arora		code	-1
On the Fairness of Disentangled Representations	Francesco Locatello, Gabriele Abbati, Thomas Rainforth, Stefan Bauer, Bernhard Schölkopf, Olivier Bachem		code	-1
Compiler Auto-Vectorization with Imitation Learning	Charith Mendis, Cambridge Yang, Yewen Pu, Saman P. Amarasinghe, Michael Carbin		code	-1
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation	Runzhe Yang, Xingyuan Sun, Karthik Narasimhan		code	-1
Exact Gaussian Processes on a Million Data Points	Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson		code	-1
Bayesian Layers: A Module for Neural Network Uncertainty	Dustin Tran, Mike Dusenberry, Mark van der Wilk, Danijar Hafner		code	-1
Learning Compositional Neural Programs with Recursive Tree Search and Planning	Thomas Pierrot, Guillaume Ligner, Scott E. Reed, Olivier Sigaud, Nicolas Perrin, Alexandre Laterre, David Kas, Karim Beguir, Nando de Freitas		code	-1
Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric	Nirandika Wanigasekara, Christina Lee Yu		code	-1
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations	Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi		code	-1
Likelihood Ratios for Out-of-Distribution Detection	Jie Ren, Peter J. Liu, Emily Fertig, Jasper Snoek, Ryan Poplin, Mark A. DePristo, Joshua V. Dillon, Balaji Lakshminarayanan		code	-1
Discrete Flows: Invertible Generative Models of Discrete Data	Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole		code	-1
A Self Validation Network for Object-Level Human Attention Estimation	Zehua Zhang, Chen Yu, David J. Crandall		code	-1
Model Selection for Contextual Bandits	Dylan J. Foster, Akshay Krishnamurthy, Haipeng Luo		code	-1
Sliced Gromov-Wasserstein	Titouan Vayer, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel		code	-1
Towards Practical Alternating Least-Squares for CCA	Zhiqiang Xu, Ping Li		code	-1
Deep Leakage from Gradients	Ligeng Zhu, Zhijian Liu, Song Han		code	-1
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness	Fanny Yang, Zuowen Wang, Christina HeinzeDeml		code	-1
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks	Spencer Frei, Yuan Cao, Quanquan Gu		code	-1
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm	Amirmassoud Farahmand		code	-1
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model	Wenbo Gong, Sebastian Tschiatschek, Sebastian Nowozin, Richard E. Turner, José Miguel HernándezLobato, Cheng Zhang		code	-1
Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors	Gauri Jagatap, Chinmay Hegde		code	-1
Planning with Goal-Conditioned Policies	Soroush Nasiriany, Vitchyr Pong, Steven Lin, Sergey Levine		code	-1
Don't take it lightly: Phasing optical random projections with unknown operators	Sidharth Gupta, Rémi Gribonval, Laurent Daudet, Ivan Dokmanic		code	-1
Generating Diverse High-Fidelity Images with VQ-VAE-2	Ali Razavi, Aäron van den Oord, Oriol Vinyals		code	-1
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs	Pedro Mercado, Francesco Tudisco, Matthias Hein		code	-1
Online Optimal Control with Linear Dynamics and Predictions: Algorithms and Regret Analysis	Yingying Li, Xin Chen, Na Li		code	-1
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption	Wei Ma, George H. Chen		code	-1
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis	Kundan Kumar, Rithesh Kumar, Thibault de Boissiere, Lucas Gestin, Wei Zhen Teoh, Jose Sotelo, Alexandre de Brébisson, Yoshua Bengio, Aaron C. Courville		code	-1
Offline Contextual Bandits with High Probability Fairness Guarantees	Blossom Metevier, Stephen Giguere, Sarah Brockman, Ari Kobren, Yuriy Brun, Emma Brunskill, Philip S. Thomas		code	-1
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods	Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee, Meisam Razaviyayn		code	-1
Semantic-Guided Multi-Attention Localization for Zero-Shot Learning	Yizhe Zhu, Jianwen Xie, Zhiqiang Tang, Xi Peng, Ahmed Elgammal		code	-1
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)	Mariya Toneva, Leila Wehbe		code	-1
Function-Space Distributions over Kernels	Gregory W. Benton, Wesley J. Maddox, Jayson P. Salkey, Julio Albinati, Andrew Gordon Wilson		code	-1
The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure For Least Squares	Rong Ge, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli		code	-1
Compositional Plan Vectors	Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine		code	-1
Locally Private Learning without Interaction Requires Separation	Amit Daniely, Vitaly Feldman		code	-1
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences	Ehsan Amid, Manfred K. Warmuth, Rohan Anil, Tomer Koren		code	-1
Computational Separations between Sampling and Optimization	Kunal Talwar		code	-1
Surfing: Iterative Optimization Over Incrementally Trained Deep Networks	Ganlin Song, Zhou Fan, John Lafferty		code	-1
Learning to Optimize in Swarms	Yue Cao, Tianlong Chen, Zhangyang Wang, Yang Shen		code	-1
On Human-Aligned Risk Minimization	Liu Leqi, Adarsh Prasad, Pradeep Ravikumar		code	-1
Semi-Parametric Efficient Policy Learning with Continuous Actions	Victor Chernozhukov, Mert Demirer, Greg Lewis, Vasilis Syrgkanis		code	-1
Multi-task Learning for Aggregated Data using Gaussian Processes	Fariba Yousefi, Michael Thomas Smith, Mauricio A. Álvarez		code	-1
Minimal Variance Sampling in Stochastic Gradient Boosting	Bulat Ibragimov, Gleb Gusev		code	-1
Beyond the Single Neuron Convex Barrier for Neural Network Certification	Gagandeep Singh, Rupanshu Ganvir, Markus Püschel, Martin T. Vechev		code	-1
An Algorithm to Learn Polytree Networks with Hidden Nodes	Firoozeh Sepehr, Donatello Materassi		code	-1
Efficiently Learning Fourier Sparse Set Functions	Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause		code	-1
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions	Peng Chen, Keyi Wu, Joshua Chen, Tom O'LearyRoseberry, Omar Ghattas		code	-1
Invariance and identifiability issues for word embeddings	Rachel Carrington, Karthik Bharath, Simon Preston		code	-1
Generalization Error Analysis of Quantized Compressive Learning	Xiaoyun Li, Ping Li		code	-1
Multi-Criteria Dimensionality Reduction with Applications to Fairness	Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie Morgenstern, Santosh S. Vempala		code	-1
Efficient Rematerialization for Deep Networks	Ravi Kumar, Manish Purohit, Zoya Svitkina, Erik Vee, Joshua R. Wang		code	-1
Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation	Samuel K. Ainsworth, Matt Barnes, Siddhartha S. Srinivasa		code	-1
Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments	Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis		code	-1
Understanding Sparse JL for Feature Hashing	Meena Jagadeesan		code	-1
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning	Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen		code	-1
Flexible Modeling of Diversity with Strongly Log-Concave Distributions	Joshua Robinson, Suvrit Sra, Stefanie Jegelka		code	-1
Momentum-Based Variance Reduction in Non-Convex SGD	Ashok Cutkosky, Francesco Orabona		code	-1
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning	Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine		code	-1
Can Unconditional Language Models Recover Arbitrary Sentences?	Nishant Subramani, Samuel R. Bowman, Kyunghyun Cho		code	-1
Group Retention when Using Machine Learning in Sequential Decision Making: the Interplay between User Dynamics and Fairness	Xueru Zhang, Mohammadmahdi Khaliligarekani, Cem Tekin, Mingyan Liu		code	-1
Faster width-dependent algorithm for mixed packing and covering LPs	Digvijay Boob, Saurabh Sawlani, Di Wang		code	-1
Flattening a Hierarchical Clustering through Active Learning	Fabio Vitale, Anand Rajagopalan, Claudio Gentile		code	-1
DeepWave: A Recurrent Neural-Network for Real-Time Acoustic Imaging	Matthieu Simeoni, Sepand Kashani, Paul Hurley, Martin Vetterli		code	-1
Certifying Geometric Robustness of Neural Networks	Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev		code	-1
Goal-conditioned Imitation Learning	Yiming Ding, Carlos Florensa, Pieter Abbeel, Mariano Phielipp		code	-1
Robust exploration in linear quadratic reinforcement learning	Jack Umenberger, Mina Ferizbegovic, Thomas B. Schön, Håkan Hjalmarsson		code	-1
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs	Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, Daisy Zhe Wang		code	-1
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration	KwangSung Jun, Ashok Cutkosky, Francesco Orabona		code	-1
Input-Output Equivalence of Unitary and Contractive RNNs	Melikasadat Emami, Mojtaba SahraeeArdakan, Sundeep Rangan, Alyson K. Fletcher		code	-1
Hamiltonian Neural Networks	Samuel Greydanus, Misko Dzamba, Jason Yosinski		code	-1
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks	Qiyang Li, Saminul Haque, Cem Anil, James Lucas, Roger B. Grosse, JörnHenrik Jacobsen		code	-1
Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks	Dina Obeid, Hugo Ramambason, Cengiz Pehlevan		code	-1
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology	Nima Dehmamy, AlbertLászló Barabási, Rose Yu		code	-1
Multiple Futures Prediction	Yichuan Charlie Tang, Ruslan Salakhutdinov		code	-1
Explicitly disentangling image content from translation and rotation with spatial-VAE	Tristan Bepler, Ellen D. Zhong, Kotaro Kelley, Edward Brignole, Bonnie Berger		code	-1
Power analysis of knockoff filters for correlated designs	Jingbo Liu, Philippe Rigollet		code	-1
A Kernel Loss for Solving the Bellman Equation	Yihao Feng, Lihong Li, Qiang Liu		code	-1
Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing	Jonas Mueller, Vasilis Syrgkanis, Matt Taddy		code	-1
Differential Privacy Has Disparate Impact on Model Accuracy	Eugene Bagdasaryan, Omid Poursaeed, Vitaly Shmatikov		code	-1
Riemannian batch normalization for SPD neural networks	Daniel A. Brooks, Olivier Schwander, Frédéric Barbaresco, JeanYves Schneider, Matthieu Cord		code	-1
Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity	Aria Wang, Michael J. Tarr, Leila Wehbe		code	-1
Stacked Capsule Autoencoders	Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton		code	-1
Learning Reward Machines for Partially Observable Reinforcement Learning	Rodrigo Toro Icarte, Ethan Waldie, Toryn Q. Klassen, Richard Anthony Valenzano, Margarita P. Castro, Sheila A. McIlraith		code	-1
Learning Representations by Maximizing Mutual Information Across Views	Philip Bachman, R. Devon Hjelm, William Buchwalter		code	-1
Amortized Bethe Free Energy Minimization for Learning MRFs	Sam Wiseman, Yoon Kim		code	-1
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity	Chulhee Yun, Suvrit Sra, Ali Jadbabaie		code	-1
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks	Aaron Voelker, Ivana Kajic, Chris Eliasmith		code	-1
Exact Combinatorial Optimization with Graph Convolutional Neural Networks	Maxime Gasse, Didier Chételat, Nicola Ferroni, Laurent Charlin, Andrea Lodi		code	-1
Fast structure learning with modular regularization	Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan		code	-1
Wasserstein Dependency Measure for Representation Learning	Sherjil Ozair, Corey Lynch, Yoshua Bengio, Aäron van den Oord, Sergey Levine, Pierre Sermanet		code	-1
TAB-VCR: Tags and Attributes based VCR Baselines	Jingxiang Lin, Unnat Jain, Alexander G. Schwing		code	-1
Universality and individuality in neural dynamics across large populations of recurrent networks	Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo		code	-1
End-to-End Learning on 3D Protein Structure for Interface Prediction	Raphael J. L. Townshend, Rishi Bedi, Patricia Suriana, Ron O. Dror		code	-1
A Family of Robust Stochastic Operators for Reinforcement Learning	Yingdong Lu, Mark S. Squillante, Chai Wah Wu		code	-1
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty	Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, Dawn Song		code	-1
Inherent Tradeoffs in Learning Fair Representations	Han Zhao, Geoffrey J. Gordon		code	-1
Are deep ResNets provably better than linear predictors?	Chulhee Yun, Suvrit Sra, Ali Jadbabaie		code	-1
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics	Niru Maheswaranathan, Alex H. Williams, Matthew D. Golub, Surya Ganguli, David Sussillo		code	-1
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos	Eleanor Batty, Matthew R. Whiteway, Shreya Saxena, Dan Biderman, Taiga Abe, Simon Musall, Winthrop Gillis, Jeffrey E. Markowitz, Anne Churchland, John P. Cunningham, Sandeep R. Datta, Scott W. Linderman, Liam Paninski		code	-1
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models	Yuge Shi, Siddharth Narayanaswamy, Brooks Paige, Philip H. S. Torr		code	-1
Gradient-based Adaptive Markov Chain Monte Carlo	Michalis K. Titsias, Petros Dellaportas		code	-1
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset	Muhammad Waleed Gondal, Manuel Wuthrich, Djordje Miladinovic, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer		code	-1
Imitation-Projected Programmatic Reinforcement Learning	Abhinav Verma, Hoang Minh Le, Yisong Yue, Swarat Chaudhuri		code	-1
Learning Data Manipulation for Augmentation and Weighting	Zhiting Hu, Bowen Tan, Ruslan Salakhutdinov, Tom M. Mitchell, Eric P. Xing		code	-1
Exploring Algorithmic Fairness in Robust Graph Covering Problems	Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, Milind Tambe		code	-1
Abstraction based Output Range Analysis for Neural Networks	Pavithra Prabhakar, Zahra Rahimi Afzal		code	-1
Space and Time Efficient Kernel Density Estimation in High Dimensions	Arturs Backurs, Piotr Indyk, Tal Wagner		code	-1
PIDForest: Anomaly Detection via Partial Identification	Parikshit Gopalan, Vatsal Sharan, Udi Wieder		code	-1
Generative Models for Graph-Based Protein Design	John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola		code	-1
The Geometry of Deep Networks: Power Diagram Subdivision	Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk		code	-1
Approximate Feature Collisions in Neural Nets	Ke Li, Tianhao Zhang, Jitendra Malik		code	-1
Ease-of-Teaching and Language Structure from Emergent Communication	Fushan Li, Michael Bowling		code	-1
Generalization in multitask deep neural classifiers: a statistical physics approach	Anthony Ndirango, Tyler Lee		code	-1
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation	Viet Anh Nguyen, Soroosh ShafieezadehAbadeh, ManChung Yue, Daniel Kuhn, Wolfram Wiesemann		code	-1
On Relating Explanations and Adversarial Examples	Alexey Ignatiev, Nina Narodytska, João MarquesSilva		code	-1
On the equivalence between graph isomorphism testing and function approximation with GNNs	Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna		code	-1
Surround Modulation: A Bio-inspired Connectivity Structure for Convolutional Neural Networks	Hosein Hasani, Mahdieh Soleymani, Hamid Aghajan		code	-1
Self-attention with Functional Time Representation Learning	Da Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan		code	-1
Re-randomized Densification for One Permutation Hashing and Bin-wise Consistent Weighted Sampling	Ping Li, Xiaoyun Li, CunHui Zhang		code	-1
Enabling hyperparameter optimization in sequential autoencoders for spiking neural data	Mohammad Reza Keshtkaran, Chethan Pandarinath		code	-1
Mixtape: Breaking the Softmax Bottleneck Efficiently	Zhilin Yang, Thang Luong, Ruslan Salakhutdinov, Quoc V. Le		code	-1