nips2016.md

NIPS2016 Paper List

论文	作者	摘要	代码	引用数
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much	Bryan D. He, Christopher De Sa, Ioannis Mitliagkas, Christopher Ré		code	-1
Deep ADMM-Net for Compressive Sensing MRI	Yan Yang, Jian Sun, Huibin Li, Zongben Xu		code	-1
A scaled Bregman theorem with applications	Richard Nock, Aditya Krishna Menon, Cheng Soon Ong		code	-1
Swapout: Learning an ensemble of deep architectures	Saurabh Singh, Derek Hoiem, David A. Forsyth		code	-1
On Regularizing Rademacher Observation Losses	Richard Nock		code	-1
Without-Replacement Sampling for Stochastic Gradient Methods	Ohad Shamir		code	-1
Fast and Provably Good Seedings for k-Means	Olivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause		code	-1
Unsupervised Learning for Physical Interaction through Video Prediction	Chelsea Finn, Ian J. Goodfellow, Sergey Levine		code	-1
High-Rank Matrix Completion and Clustering under Self-Expressive Models	Ehsan Elhamifar		code	-1
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling	Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, Josh Tenenbaum		code	-1
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks	Tianfan Xue, Jiajun Wu, Katherine L. Bouman, Bill Freeman		code	-1
Human Decision-Making under Limited Time	Pedro A. Ortega, Alan A. Stocker		code	-1
Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition	Shizhong Han, Zibo Meng, AhmedShehab Khan, Yan Tong		code	-1
Natural-Parameter Networks: A Class of Probabilistic Neural Networks	Hao Wang, Xingjian Shi, DitYan Yeung		code	-1
Tree-Structured Reinforcement Learning for Sequential Object Localization	Zequn Jie, Xiaodan Liang, Jiashi Feng, Xiaojie Jin, Wen Feng Lu, Shuicheng Yan		code	-1
Unsupervised Domain Adaptation with Residual Transfer Networks	Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan		code	-1
Verification Based Solution for Structured MAB Problems	Zohar S. Karnin		code	-1
Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games	Maximilian Balandat, Walid Krichene, Claire J. Tomlin, Alexandre M. Bayen		code	-1
Linear dynamical neural population models through nonlinear embeddings	Yuanjun Gao, Evan W. Archer, Liam Paninski, John P. Cunningham		code	-1
SURGE: Surface Regularized Geometry Estimation from a Single Image	Peng Wang, Xiaohui Shen, Bryan C. Russell, Scott Cohen, Brian L. Price, Alan L. Yuille		code	-1
Interpretable Distribution Features with Maximum Testing Power	Wittawat Jitkrittum, Zoltán Szabó, Kacper P. Chwialkowski, Arthur Gretton		code	-1
Sorting out typicality with the inverse moment matrix SOS polynomial	Edouard Pauwels, Jean B. Lasserre		code	-1
Multi-armed Bandits: Competing with Optimal Sequences	Zohar S. Karnin, Oren Anava		code	-1
Multivariate tests of association based on univariate tests	Ruth Heller, Yair Heller		code	-1
Learning What and Where to Draw	Scott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee		code	-1
The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM	Damek Davis, Brent Edmunds, Madeleine Udell		code	-1
Integrated perception with recurrent multi-task neural networks	Hakan Bilen, Andrea Vedaldi		code	-1
Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs	YuXiong Wang, Martial Hebert		code	-1
CNNpack: Packing Convolutional Neural Networks in the Frequency Domain	Yunhe Wang, Chang Xu, Shan You, Dacheng Tao, Chao Xu		code	-1
Cooperative Graphical Models	Josip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause		code	-1
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization	Sebastian Nowozin, Botond Cseke, Ryota Tomioka		code	-1
Bayesian Optimization for Probabilistic Programs	Tom Rainforth, Tuan Anh Le, JanWillem van de Meent, Michael A. Osborne, Frank D. Wood		code	-1
Hierarchical Question-Image Co-Attention for Visual Question Answering	Jiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh		code	-1
Optimal Sparse Linear Encoders and Sparse PCA	Malik MagdonIsmail, Christos Boutsidis		code	-1
FPNN: Field Probing Neural Networks for 3D Data	Yangyan Li, Sören Pirk, Hao Su, Charles Ruizhongtai Qi, Leonidas J. Guibas		code	-1
CRF-CNN: Modeling Structured Information in Human Pose Estimation	Xiao Chu, Wanli Ouyang, Hongsheng Li, Xiaogang Wang		code	-1
Fairness in Learning: Classic and Contextual Bandits	Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Aaron Roth		code	-1
Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization	Alexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy		code	-1
Domain Separation Networks	Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan		code	-1
DISCO Nets : DISsimilarity COefficients Networks	Diane Bouchacourt, Pawan Kumar Mudigonda, Sebastian Nowozin		code	-1
Multimodal Residual Learning for Visual QA	JinHwa Kim, SangWoo Lee, DongHyun Kwak, MinOh Heo, Jeonghee Kim, JungWoo Ha, ByoungTak Zhang		code	-1
CMA-ES with Optimal Covariance Update and Storage Complexity	Oswin Krause, Dídac Rodríguez Arbonès, Christian Igel		code	-1
R-FCN: Object Detection via Region-based Fully Convolutional Networks	Jifeng Dai, Yi Li, Kaiming He, Jian Sun		code	-1
GAP Safe Screening Rules for Sparse-Group Lasso	Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon		code	-1
Learning and Forecasting Opinion Dynamics in Social Networks	Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel GomezRodriguez		code	-1
Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares	Rong Zhu		code	-1
Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks	Hao Wang, Xingjian Shi, DitYan Yeung		code	-1
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula	Jean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová		code	-1
A Unified Approach for Learning the Parameters of Sum-Product Networks	Han Zhao, Pascal Poupart, Geoffrey J. Gordon		code	-1
Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images	Junhua Mao, Jiajing Xu, Yushi Jing, Alan L. Yuille		code	-1
Stochastic Online AUC Maximization	Yiming Ying, Longyin Wen, Siwei Lyu		code	-1
The Generalized Reparameterization Gradient	Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei		code	-1
Coupled Generative Adversarial Networks	MingYu Liu, Oncel Tuzel		code	-1
Exponential Family Embeddings	Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei		code	-1
Variational Information Maximization for Feature Selection	Shuyang Gao, Greg Ver Steeg, Aram Galstyan		code	-1
Operator Variational Inference	Rajesh Ranganath, Dustin Tran, Jaan Altosaar, David M. Blei		code	-1
Fast learning rates with heavy-tailed losses	Vu C. Dinh, Lam Si Tung Ho, Binh T. Nguyen, Duy M. H. Nguyen		code	-1
Budgeted stream-based active learning via adaptive submodular maximization	Kaito Fujii, Hisashi Kashima		code	-1
Learning feed-forward one-shot learners	Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi		code	-1
Learning User Perceived Clusters with Feature-Level Supervision	TingYu Cheng, Guiguan Lin, Xinyang Gong, KangJun Liu, ShanHung Wu		code	-1
Robust Spectral Detection of Global Structures in the Data by Learning a Regularization	Pan Zhang		code	-1
Residual Networks Behave Like Ensembles of Relatively Shallow Networks	Andreas Veit, Michael J. Wilber, Serge J. Belongie		code	-1
Adversarial Multiclass Classification: A Risk Minimization Perspective	Rizal Fathony, Anqi Liu, Kaiser Asif, Brian D. Ziebart		code	-1
Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient Flow	Gang Wang, Georgios B. Giannakis		code	-1
Coin Betting and Parameter-Free Online Learning	Francesco Orabona, Dávid Pál		code	-1
Deep Learning without Poor Local Minima	Kenji Kawaguchi		code	-1
Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity	Eugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko		code	-1
A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++	Dennis Wei		code	-1
Generating Videos with Scene Dynamics	Carl Vondrick, Hamed Pirsiavash, Antonio Torralba		code	-1
Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks	Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman		code	-1
A Powerful Generative Model Using Random Weights for the Deep Image Representation	Kun He, Yan Wang, John E. Hopcroft		code	-1
Optimizing affinity-based binary hashing using auxiliary coordinates	Ramin Raziperchikolaei, Miguel Á. CarreiraPerpiñán		code	-1
Double Thompson Sampling for Dueling Bandits	Huasen Wu, Xin Liu		code	-1
Generating Images with Perceptual Similarity Metrics based on Deep Networks	Alexey Dosovitskiy, Thomas Brox		code	-1
Dynamic Filter Networks	Xu Jia, Bert De Brabandere, Tinne Tuytelaars, Luc Van Gool		code	-1
A Simple Practical Accelerated Method for Finite Sums	Aaron Defazio		code	-1
Barzilai-Borwein Step Size for Stochastic Gradient Descent	Conghui Tan, Shiqian Ma, YuHong Dai, Yuqiu Qian		code	-1
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability	Guillaume Papa, Aurélien Bellet, Stéphan Clémençon		code	-1
Optimal spectral transportation with application to music transcription	Rémi Flamary, Cédric Févotte, Nicolas Courty, Valentin Emiya		code	-1
Regularized Nonlinear Acceleration	Damien Scieur, Alexandre d'Aspremont, Francis R. Bach		code	-1
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling	Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros		code	-1
Single-Image Depth Perception in the Wild	Weifeng Chen, Zhao Fu, Dawei Yang, Jia Deng		code	-1
Computational and Statistical Tradeoffs in Learning to Rank	Ashish Khetan, Sewoong Oh		code	-1
Online Convex Optimization with Unconstrained Domains and Losses	Ashok Cutkosky, Kwabena Boahen		code	-1
An ensemble diversity approach to supervised binary hashing	Miguel Á. CarreiraPerpiñán, Ramin Raziperchikolaei		code	-1
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis	Weiran Wang, Jialei Wang, Dan Garber, Nati Srebro		code	-1
The Power of Adaptivity in Identifying Statistical Alternatives	Kevin G. Jamieson, Daniel Haas, Benjamin Recht		code	-1
On Explore-Then-Commit strategies	Aurélien Garivier, Tor Lattimore, Emilie Kaufmann		code	-1
Sublinear Time Orthogonal Tensor Decomposition	Zhao Song, David P. Woodruff, Huan Zhang		code	-1
DECOrrelated feature space partitioning for distributed sparse regression	Xiangyu Wang, David B. Dunson, Chenlei Leng		code	-1
Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition	Jinzhuo Wang, Wenmin Wang, Xiongtao Chen, Ronggang Wang, Wen Gao		code	-1
Dual Learning for Machine Translation	Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, TieYan Liu, WeiYing Ma		code	-1
Dialog-based Language Learning	Jason Weston		code	-1
Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition	Théodore Bluche		code	-1
Temporal Regularized Matrix Factorization for High-dimensional Time Series Prediction	HsiangFu Yu, Nikhil Rao, Inderjit S. Dhillon		code	-1
Active Nearest-Neighbor Learning in Metric Spaces	Aryeh Kontorovich, Sivan Sabato, Ruth Urner		code	-1
Proximal Deep Structured Models	Shenlong Wang, Sanja Fidler, Raquel Urtasun		code	-1
Faster Projection-free Convex Optimization over the Spectrahedron	Dan Garber		code	-1
Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach	Rémi Lam, Karen Willcox, David H. Wolpert		code	-1
SoundNet: Learning Sound Representations from Unlabeled Video	Yusuf Aytar, Carl Vondrick, Antonio Torralba		code	-1
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks	Tim Salimans, Diederik P. Kingma		code	-1
Efficient Second Order Online Learning by Sketching	Haipeng Luo, Alekh Agarwal, Nicolò CesaBianchi, John Langford		code	-1
Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis	Yoshinobu Kawahara		code	-1
Distributed Flexible Nonlinear Tensor Factorization	Shandian Zhe, Kai Zhang, Pengyuan Wang, Kuangchih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani		code	-1
The Robustness of Estimator Composition	Pingfan Tang, Jeff M. Phillips		code	-1
Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats	Bipin Rajendran, Pulkit Tandon, Yash H. Malviya		code	-1
PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions	Mikhail Figurnov, Aizhan Ibraimova, Dmitry P. Vetrov, Pushmeet Kohli		code	-1
Differential Privacy without Sensitivity	Kentaro Minami, Hiromi Arai, Issei Sato, Hiroshi Nakagawa		code	-1
Optimal Cluster Recovery in the Labeled Stochastic Block Model	SeYoung Yun, Alexandre Proutière		code	-1
Even Faster SVD Decomposition Yet Without Agonizing Pain	Zeyuan Allen Zhu, Yuanzhi Li		code	-1
An algorithm for L1 nearest neighbor search via monotonic embedding	Xinan Wang, Sanjoy Dasgupta		code	-1
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations	Kirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos		code	-1
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes	Dan Garber, Ofer Meshi		code	-1
Efficient Nonparametric Smoothness Estimation	Shashank Singh, Simon S. Du, Barnabás Póczos		code	-1
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks	Yarin Gal, Zoubin Ghahramani		code	-1
Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation	George Papamakarios, Iain Murray		code	-1
Direct Feedback Alignment Provides Learning in Deep Neural Networks	Arild Nøkland		code	-1
Safe and Efficient Off-Policy Reinforcement Learning	Rémi Munos, Tom Stepleton, Anna Harutyunyan, Marc G. Bellemare		code	-1
A Multi-Batch L-BFGS Method for Machine Learning	Albert S. Berahas, Jorge Nocedal, Martin Takác		code	-1
Semiparametric Differential Graph Models	Pan Xu, Quanquan Gu		code	-1
Rényi Divergence Variational Inference	Yingzhen Li, Richard E. Turner		code	-1
Doubly Convolutional Neural Networks	Shuangfei Zhai, Yu Cheng, Zhongfei (Mark) Zhang, Weining Lu		code	-1
Density Estimation via Discrepancy Based Adaptive Sequential Partition	Dangna Li, Kun Yang, Wing Hung Wong		code	-1
How Deep is the Feature Analysis underlying Rapid Visual Categorization?	Sven Eberhardt, Jonah G. Cader, Thomas Serre		code	-1
VIME: Variational Information Maximizing Exploration	Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel		code	-1
Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain	Timothy N. Rubin, Oluwasanmi Koyejo, Michael N. Jones, Tal Yarkoni		code	-1
Solving Marginal MAP Problems with NP Oracles and Parity Constraints	Yexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P. Gomes, Bart Selman		code	-1
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models	Tomoharu Iwata, Makoto Yamada		code	-1
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization	Sashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola		code	-1
Variance Reduction in Stochastic Gradient Langevin Dynamics	Kumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing		code	-1
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning	Mehdi Sajjadi, Mehran Javanmardi, Tolga Tasdizen		code	-1
Dense Associative Memory for Pattern Recognition	Dmitry Krotov, John J. Hopfield		code	-1
Causal Bandits: Learning Good Interventions via Causal Inference	Finnian Lattimore, Tor Lattimore, Mark D. Reid		code	-1
Refined Lower Bounds for Adversarial Bandits	Sébastien Gerchinovitz, Tor Lattimore		code	-1
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning	Gang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, Masashi Sugiyama		code	-1
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/\epsilon)	Yi Xu, Yan Yan, Qihang Lin, Tianbao Yang		code	-1
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators	Shashank Singh, Barnabás Póczos		code	-1
A state-space model of cross-region dynamic connectivity in MEG/EEG	Ying Yang, Elissa Aminoff, Michael J. Tarr, Robert E. Kass		code	-1
What Makes Objects Similar: A Unified Multi-Metric Learning Approach	HanJia Ye, DeChuan Zhan, XueMin Si, Yuan Jiang, ZhiHua Zhou		code	-1
Adaptive Maximization of Pointwise Submodular Functions With Budget Constraint	Nguyen Cuong, Huan Xu		code	-1
Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions	Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal		code	-1
Local Similarity-Aware Deep Feature Embedding	Chen Huang, Chen Change Loy, Xiaoou Tang		code	-1
A Communication-Efficient Parallel Algorithm for Decision Tree	Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, TieYan Liu		code	-1
Convex Two-Layer Modeling with Latent Structure	Vignesh Ganapathiraman, Xinhua Zhang, Yaoliang Yu, Junfeng Wen		code	-1
Sampling for Bayesian Program Learning	Kevin Ellis, Armando SolarLezama, Josh Tenenbaum		code	-1
Learning Kernels with Random Features	Aman Sinha, John C. Duchi		code	-1
Optimal Tagging with Markov Chain Optimization	Nir Rosenfeld, Amir Globerson		code	-1
Crowdsourced Clustering: Querying Edges vs Triangles	Ramya Korlakai Vinayak, Babak Hassibi		code	-1
Mixed vine copulas as joint models of spike counts and local field potentials	Arno Onken, Stefano Panzeri		code	-1
Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation	Emmanuel Abbe, Colin Sandon		code	-1
Adaptive Concentration Inequalities for Sequential Decision Problems	Shengjia Zhao, Enze Zhou, Ashish Sabharwal, Stefano Ermon		code	-1
Nested Mini-Batch K-Means	James Newling, François Fleuret		code	-1
Deep Learning Models of the Retinal Response to Natural Scenes	Lane McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen Baccus		code	-1
Preference Completion from Partial Rankings	Suriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh		code	-1
Dynamic Network Surgery for Efficient DNNs	Yiwen Guo, Anbang Yao, Yurong Chen		code	-1
Learning a Metric Embedding for Face Recognition using the Multibatch Method	Oren Tadmor, Tal Rosenwein, Shai ShalevShwartz, Yonatan Wexler, Amnon Shashua		code	-1
A Pseudo-Bayesian Algorithm for Robust PCA	TaeHyun Oh, Yasuyuki Matsushita, InSo Kweon, David P. Wipf		code	-1
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks	Julien Mairal		code	-1
Stochastic Variance Reduction Methods for Saddle-Point Problems	Balamurugan Palaniappan, Francis R. Bach		code	-1
Flexible Models for Microclustering with Application to Entity Resolution	Brenda Betancourt, Giacomo Zanella, Jeffrey W. Miller, Hanna M. Wallach, Abbas Zaidi, Beka Steorts		code	-1
Catching heuristics are optimal control policies	Boris Belousov, Gerhard Neumann, Constantin A. Rothkopf, Jan Peters		code	-1
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian	Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel		code	-1
Adaptive Neural Compilation	Rudy Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr		code	-1
Synthesis of MCMC and Belief Propagation	Sungsoo Ahn, Michael Chertkov, Jinwoo Shin		code	-1
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables	Mauro Scanagatta, Giorgio Corani, Cassio P. de Campos, Marco Zaffalon		code	-1
Unifying Count-Based Exploration and Intrinsic Motivation	Marc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos		code	-1
Large Margin Discriminant Dimensionality Reduction in Prediction Space	Mohammad J. Saberian, José Costa Pereira, Nuno Vasconcelos, Can Xu		code	-1
Stochastic Structured Prediction under Bandit Feedback	Artem Sokolov, Julia Kreutzer, Stefan Riezler, Christopher Lo		code	-1
Simple and Efficient Weighted Minwise Hashing	Anshumali Shrivastava		code	-1
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation	Ilija Bogunovic, Jonathan Scarlett, Andreas Krause, Volkan Cevher		code	-1
Structured Sparse Regression via Greedy Hard Thresholding	Prateek Jain, Nikhil Rao, Inderjit S. Dhillon		code	-1
Understanding Probabilistic Sparse Gaussian Process Approximations	Matthias Bauer, Mark van der Wilk, Carl Edward Rasmussen		code	-1
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques	Elad Richardson, Rom Herskovitz, Boris Ginsburg, Michael Zibulevsky		code	-1
Generating Long-term Trajectories Using Deep Hierarchical Networks	Stephan Zheng, Yisong Yue, Jennifer A. Hobbs		code	-1
Learning Tree Structured Potential Games	Vikas K. Garg, Tommi S. Jaakkola		code	-1
Observational-Interventional Priors for Dose-Response Learning	Ricardo Silva		code	-1
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs	Shahin Jabbari, Ryan M. Rogers, Aaron Roth, Zhiwei Steven Wu		code	-1
Identification and Overidentification of Linear Structural Equation Models	Bryant Chen		code	-1
Adaptive Skills Adaptive Partitions (ASAP)	Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor		code	-1
Multiple-Play Bandits in the Position-Based Model	Paul Lagrée, Claire Vernade, Olivier Cappé		code	-1
Optimal Black-Box Reductions Between Optimization Objectives	Zeyuan Allen Zhu, Elad Hazan		code	-1
On Valid Optimal Assignment Kernels and Applications to Graph Classification	Nils M. Kriege, PierreLouis Giscard, Richard C. Wilson		code	-1
Robustness of classifiers: from adversarial to random noise	Alhussein Fawzi, SeyedMohsen MoosaviDezfooli, Pascal Frossard		code	-1
A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing	Ming Lin, Jieping Ye		code	-1
Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters	Zeyuan Allen Zhu, Yang Yuan, Karthik Sridharan		code	-1
Combinatorial Multi-Armed Bandit with General Reward Functions	Wei Chen, Wei Hu, Fu Li, Jian Li, Yu Liu, Pinyan Lu		code	-1
Boosting with Abstention	Corinna Cortes, Giulia DeSalvo, Mehryar Mohri		code	-1
Regret of Queueing Bandits	Subhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai		code	-1
Deep Learning Games	Dale Schuurmans, Martin Zinkevich		code	-1
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods	Antoine Gautier, Quynh Nguyen, Matthias Hein		code	-1
Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision	Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee		code	-1
A Credit Assignment Compiler for Joint Prediction	KaiWei Chang, He He, Stéphane Ross, Hal Daumé III, John Langford		code	-1
Accelerating Stochastic Composition Optimization	Mengdi Wang, Ji Liu, Ethan X. Fang		code	-1
Reward Augmented Maximum Likelihood for Neural Structured Prediction	Mohammad Norouzi, Samy Bengio, Zhifeng Chen, Navdeep Jaitly, Mike Schuster, Yonghui Wu, Dale Schuurmans		code	-1
Consistent Kernel Mean Estimation for Functions of Random Variables	CarlJohann SimonGabriel, Adam Scibior, Ilya O. Tolstikhin, Bernhard Schölkopf		code	-1
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling	Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin		code	-1
Scalable Adaptive Stochastic Optimization Using Random Projections	Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen		code	-1
Variational Inference in Mixed Probabilistic Submodular Models	Josip Djolonga, Sebastian Tschiatschek, Andreas Krause		code	-1
Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated	Namrata Vaswani, Han Guo		code	-1
The Multi-fidelity Multi-armed Bandit	Kirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider		code	-1
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm	Kejun Huang, Xiao Fu, Nikos D. Sidiropoulos		code	-1
Bootstrap Model Aggregation for Distributed Statistical Learning	Jun Han, Qiang Liu		code	-1
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification	Steven ChengXian Li, Benjamin M. Marlin		code	-1
A Bandit Framework for Strategic Regression	Yang Liu, Yiling Chen		code	-1
Architectural Complexity Measures of Recurrent Neural Networks	Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio		code	-1
Statistical Inference for Cluster Trees	Jisu Kim, YenChi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry A. Wasserman		code	-1
PAC Reinforcement Learning with Rich Observations	Akshay Krishnamurthy, Alekh Agarwal, John Langford		code	-1
Improved Deep Metric Learning with Multi-class N-pair Loss Objective	Kihyuk Sohn		code	-1
Unsupervised Learning of Spoken Language with Visual Context	David F. Harwath, Antonio Torralba, James R. Glass		code	-1
Low-Rank Regression with Tensor Responses	Guillaume Rabusseau, Hachem Kadri		code	-1
PAC-Bayesian Theory Meets Bayesian Inference	Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon LacosteJulien		code	-1
Data Poisoning Attacks on Factorization-Based Collaborative Filtering	Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik		code	-1
Learned Region Sparsity and Diversity Also Predicts Visual Attention	Zijun Wei, Hossein Adeli, Minh Hoai, Gregory J. Zelinsky, Dimitris Samaras		code	-1
End-to-End Goal-Driven Web Navigation	Rodrigo Frassetto Nogueira, Kyunghyun Cho		code	-1
Automated scalable segmentation of neurons from multispectral images	Uygar Sümbül, Douglas H. Roossien, Dawen Cai, Fei Chen, Nicholas Barry, John P. Cunningham, Edward S. Boyden, Liam Paninski		code	-1
Privacy Odometers and Filters: Pay-as-you-Go Composition	Ryan M. Rogers, Salil P. Vadhan, Aaron Roth, Jonathan R. Ullman		code	-1
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels	Ilya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf		code	-1
Adaptive optimal training of animal behavior	Ji Hyun Bak, Jung Choi, Ilana Witten, Athena Akrami, Jonathan W. Pillow		code	-1
Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition	Seyed Hamidreza Kasaei, Ana Maria Tomé, Luís Seabra Lopes		code	-1
Relevant sparse codes with variational information bottleneck	Matthew Chalk, Olivier Marre, Gasper Tkacik		code	-1
Combinatorial Energy Learning for Image Segmentation	Jeremy B. MaitinShepard, Viren Jain, Michal Januszewski, Peter Li, Pieter Abbeel		code	-1
Orthogonal Random Features	Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. HoltmannRice, Sanjiv Kumar		code	-1
Fast Active Set Methods for Online Spike Inference from Calcium Imaging	Johannes Friedrich, Liam Paninski		code	-1
Diffusion-Convolutional Neural Networks	James Atwood, Don Towsley		code	-1
Bayesian latent structure discovery from multi-neuron recordings	Scott W. Linderman, Ryan P. Adams, Jonathan W. Pillow		code	-1
A Probabilistic Programming Approach To Probabilistic Data Analysis	Feras Saad, Vikash K. Mansinghka		code	-1
A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics	William Hoiles, Mihaela van der Schaar		code	-1
Inference by Reparameterization in Neural Population Codes	Rajkumar Vasudeva Raju, Xaq Pitkow		code	-1
Tensor Switching Networks	ChuanYung Tsai, Andrew M. Saxe, David D. Cox		code	-1
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo	Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël Richard		code	-1
Coordinate-wise Power Method	Qi Lei, Kai Zhong, Inderjit S. Dhillon		code	-1
Learning Influence Functions from Incomplete Observations	Xinran He, Ke Xu, David Kempe, Yan Liu		code	-1
Learning Structured Sparsity in Deep Neural Networks	Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, Hai Li		code	-1
Sample Complexity of Automated Mechanism Design	MariaFlorina Balcan, Tuomas Sandholm, Ellen Vitercik		code	-1
Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot Products	Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover		code	-1
Brains on Beats	Umut Güçlü, Jordy Thielen, Michael Hanke, Marcel van Gerven, Marcel A. J. van Gerven		code	-1
Learning Transferrable Representations for Unsupervised Domain Adaptation	Ozan Sener, Hyun Oh Song, Ashutosh Saxena, Silvio Savarese		code	-1
Stochastic Multiple Choice Learning for Training Diverse Deep Ensembles	Stefan Lee, Senthil Purushwalkam, Michael Cogswell, Viresh Ranjan, David J. Crandall, Dhruv Batra		code	-1
Active Learning from Imperfect Labelers	Songbai Yan, Kamalika Chaudhuri, Tara Javidi		code	-1
Learning to Communicate with Deep Multi-Agent Reinforcement Learning	Jakob N. Foerster, Yannis M. Assael, Nando de Freitas, Shimon Whiteson		code	-1
Value Iteration Networks	Aviv Tamar, Sergey Levine, Pieter Abbeel, Yi Wu, Garrett Thomas		code	-1
Blind Regression: Nonparametric Regression for Latent Variable Models via Collaborative Filtering	Dogyoon Song, Christina E. Lee, Yihua Li, Devavrat Shah		code	-1
On the Recursive Teaching Dimension of VC Classes	Xi Chen, Yu Cheng, Bo Tang		code	-1
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel		code	-1
Hardness of Online Sleeping Combinatorial Optimization Problems	Satyen Kale, Chansoo Lee, Dávid Pál		code	-1
Mixed Linear Regression with Multiple Components	Kai Zhong, Prateek Jain, Inderjit S. Dhillon		code	-1
Sequential Neural Models with Stochastic Layers	Marco Fraccaro, Søren Kaae Sønderby, Ulrich Paquet, Ole Winther		code	-1
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences	Hongseok Namkoong, John C. Duchi		code	-1
Minimizing Quadratic Functions in Constant Time	Kohei Hayashi, Yuichi Yoshida		code	-1
Improved Techniques for Training GANs	Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen		code	-1
DeepMath - Deep Sequence Models for Premise Selection	Geoffrey Irving, Christian Szegedy, Alexander A. Alemi, Niklas Eén, François Chollet, Josef Urban		code	-1
Learning Multiagent Communication with Backpropagation	Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus		code	-1
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity	Amit Daniely, Roy Frostig, Yoram Singer		code	-1
Learning the Number of Neurons in Deep Networks	Jose M. Alvarez, Mathieu Salzmann		code	-1
Finding significant combinations of features in the presence of categorical covariates	Laetitia Papaxanthos, Felipe LlinaresLópez, Dean A. Bodenham, Karsten M. Borgwardt		code	-1
Examples are not enough, learn to criticize! Criticism for Interpretability	Been Kim, Oluwasanmi Koyejo, Rajiv Khanna		code	-1
Optimistic Bandit Convex Optimization	Scott Yang, Mehryar Mohri		code	-1
Safe Policy Improvement by Minimizing Robust Baseline Regret	Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow		code	-1
Graphons, mergeons, and so on!	Justin Eldridge, Mikhail Belkin, Yusu Wang		code	-1
Hierarchical Clustering via Spreading Metrics	Aurko Roy, Sebastian Pokutta		code	-1
Learning Bayesian networks with ancestral constraints	Eunice YuhJie Chen, Yujia Shen, Arthur Choi, Adnan Darwiche		code	-1
Pruning Random Forests for Prediction on a Budget	Feng Nan, Joseph Wang, Venkatesh Saligrama		code	-1
Clustering with Bregman Divergences: an Asymptotic Analysis	Chaoyue Liu, Mikhail Belkin		code	-1
Variational Autoencoder for Deep Learning of Images, Labels and Captions	Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin		code	-1
Review Networks for Caption Generation	Zhilin Yang, Ye Yuan, Yuexin Wu, William W. Cohen, Ruslan Salakhutdinov		code	-1
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm	Qiang Liu, Dilin Wang		code	-1
A Bio-inspired Redundant Sensing Architecture	Anh Tuan Nguyen, Jian Xu, Zhi Yang		code	-1
Contextual semibandits via supervised learning oracles	Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudík		code	-1
Blind Attacks on Machine Learners	Alex Beatson, Zhaoran Wang, Han Liu		code	-1
Universal Correspondence Network	Christopher B. Choy, JunYoung Gwak, Silvio Savarese, Manmohan Krishna Chandraker		code	-1
Satisfying Real-world Goals with Dataset Constraints	Gabriel Goh, Andrew Cotter, Maya R. Gupta, Michael P. Friedlander		code	-1
Deep Learning for Predicting Human Strategic Behavior	Jason S. Hartford, James R. Wright, Kevin LeytonBrown		code	-1
Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games	Sougata Chaudhuri, Ambuj Tewari		code	-1
Eliciting Categorical Data for Optimal Aggregation	ChienJu Ho, Rafael M. Frongillo, Yiling Chen		code	-1
Measuring the reliability of MCMC inference with bidirectional Monte Carlo	Roger B. Grosse, Siddharth Ancha, Daniel M. Roy		code	-1
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation	Weihao Gao, Sewoong Oh, Pramod Viswanath		code	-1
Selective inference for group-sparse linear models	Fan Yang, Rina Foygel Barber, Prateek Jain, John D. Lafferty		code	-1
Graph Clustering: Block-models and model free results	Yali Wan, Marina Meila		code	-1
Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution	Christopher Lynn, Daniel D. Lee		code	-1
Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease	Hao Henry Zhou, Vamsi K. Ithapu, Sathya Narayanan Ravi, Vikas Singh, Grace Wahba, Sterling C. Johnson		code	-1
Geometric Dirichlet Means Algorithm for topic inference	Mikhail Yurochkin, XuanLong Nguyen		code	-1
Structured Prediction Theory Based on Factor Graph Complexity	Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Scott Yang		code	-1
Improved Dropout for Shallow and Deep Learning	Zhe Li, Boqing Gong, Tianbao Yang		code	-1
Constraints Based Convex Belief Propagation	Yaniv Tenzer, Alexander G. Schwing, Kevin Gimpel, Tamir Hazan		code	-1
Error Analysis of Generalized Nyström Kernel Regression	Hong Chen, Haifeng Xia, Heng Huang, Weidong Cai		code	-1
A Probabilistic Framework for Deep Learning	Ankit B. Patel, Minh Tan Nguyen, Richard G. Baraniuk		code	-1
General Tensor Spectral Co-clustering for Higher-Order Data	Tao Wu, Austin R. Benson, David F. Gleich		code	-1
Single Pass PCA of Matrix Products	Shanshan Wu, Srinadh Bhojanapalli, Sujay Sanghavi, Alexandros G. Dimakis		code	-1
Stochastic Variational Deep Kernel Learning	Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov, Eric P. Xing		code	-1
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models	Marc Vuffray, Sidhant Misra, Andrey Y. Lokhov, Michael Chertkov		code	-1
Long-term Causal Effects via Behavioral Game Theory	Panagiotis Toulis, David C. Parkes		code	-1
Measuring Neural Net Robustness with Constraints	Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya V. Nori, Antonio Criminisi		code	-1
Reshaped Wirtinger Flow for Solving Quadratic System of Equations	Huishuai Zhang, Yingbin Liang		code	-1
Nearly Isometric Embedding by Relaxation	James McQueen, Marina Meila, Dominique Joncas		code	-1
Probabilistic Inference with Generating Functions for Poisson Latent Variable Models	Kevin Winner, Daniel Sheldon		code	-1
Causal meets Submodular: Subset Selection with Directed Information	Yuxun Zhou, Costas J. Spanos		code	-1
Depth from a Single Image by Harmonizing Overcomplete Local Network Predictions	Ayan Chakrabarti, Jingyu Shao, Greg Shakhnarovich		code	-1
Deep Neural Networks with Inexact Matching for Person Re-Identification	Arulkumar Subramaniam, Moitreya Chatterjee, Anurag Mittal		code	-1
Global Analysis of Expectation Maximization for Mixtures of Two Gaussians	Ji Xu, Daniel J. Hsu, Arian Maleki		code	-1
Estimating the class prior and posterior from noisy positives and unlabeled data	Shantanu Jain, Martha White, Predrag Radivojac		code	-1
Kronecker Determinantal Point Processes	Zelda E. Mariet, Suvrit Sra		code	-1
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding	Lalit Jain, Kevin G. Jamieson, Robert D. Nowak		code	-1
Feature-distributed sparse regression: a screen-and-clean approach	Jiyan Yang, Michael W. Mahoney, Michael A. Saunders, Yuekai Sun		code	-1
Learning Bound for Parameter Transfer Learning	Wataru Kumagai		code	-1
Learning under uncertainty: a comparison between R-W and Bayesian approach	He Huang, Martin P. Paulus		code	-1
Bi-Objective Online Matching and Submodular Allocations	Hossein Esfandiari, Nitish Korula, Vahab S. Mirrokni		code	-1
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity	Ping Li, Michael Mitzenmacher, Martin Slawski		code	-1
The non-convex Burer-Monteiro approach works on smooth semidefinite programs	Nicolas Boumal, Vladislav Voroninski, Afonso S. Bandeira		code	-1
Dimensionality Reduction of Massive Sparse Datasets Using Coresets	Dan Feldman, Mikhail Volkov, Daniela Rus		code	-1
Using Social Dynamics to Make Individual Predictions: Variational Inference with a Stochastic Kinetic Model	Zhen Xu, Wen Dong, Sargur N. Srihari		code	-1
Supervised learning through the lens of compression	Ofir David, Shay Moran, Amir Yehudayoff		code	-1
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data	Xinghua Lou, Ken Kansky, Wolfgang Lehrach, C. C. Laan, Bhaskara Marthi, D. Scott Phoenix, Dileep George		code	-1
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip Connections	XiaoJiao Mao, Chunhua Shen, YuBin Yang		code	-1
Object based Scene Representations using Fisher Scores of Local Subspace Projections	Mandar Dixit, Nuno Vasconcelos		code	-1
Active Learning with Oracle Epiphany	TzuKuo Huang, Lihong Li, Ara Vartanian, Saleema Amershi, Xiaojin Zhu		code	-1
Statistical Inference for Pairwise Graphical Models Using Score Matching	Ming Yu, Mladen Kolar, Varun Gupta		code	-1
Improved Error Bounds for Tree Representations of Metric Spaces	Samir Chowdhury, Facundo Mémoli, Zane T. Smith		code	-1
Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?	Arturo Deza, Miguel P. Eckstein		code	-1
On Multiplicative Integration with Recurrent Neural Networks	Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov		code	-1
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices	Kirthevasan Kandasamy, Maruan AlShedivat, Eric P. Xing		code	-1
Regret Bounds for Non-decomposable Metrics with Missing Labels	Nagarajan Natarajan, Prateek Jain		code	-1
Robust k-means: a Theoretical Revisit	Alexandros Georgogiannis		code	-1
Bayesian optimization for automated model selection	Gustavo Malkomes, Chip Schaff, Roman Garnett		code	-1
A Probabilistic Model of Social Decision Making based on Reward Maximization	Koosha Khalvati, Seongmin A. Park, JeanClaude Dreher, Rajesh P. Rao		code	-1
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition	Ahmed M. Alaa, Mihaela van der Schaar		code	-1
Fast and Flexible Monotonic Functions with Ensembles of Lattices	Mahdi Milani Fard, Kevin Robert Canini, Andrew Cotter, Jan Pfeifer, Maya R. Gupta		code	-1
Conditional Generative Moment-Matching Networks	Yong Ren, Jun Zhu, Jialian Li, Yucen Luo		code	-1
Stochastic Gradient MCMC with Stale Gradients	Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin		code	-1
Composing graphical models with neural networks for structured representations and fast inference	Matthew J. Johnson, David Duvenaud, Alexander B. Wiltschko, Ryan P. Adams, Sandeep R. Datta		code	-1
Noise-Tolerant Life-Long Matrix Completion via Adaptive Sampling	MariaFlorina Balcan, Hongyang Zhang		code	-1
Combinatorial semi-bandit with known covariance	Rémy Degenne, Vianney Perchet		code	-1
Matrix Completion has No Spurious Local Minimum	Rong Ge, Jason D. Lee, Tengyu Ma		code	-1
The Multiscale Laplacian Graph Kernel	Risi Kondor, Horace Pan		code	-1
Adaptive Averaging in Accelerated Descent Dynamics	Walid Krichene, Alexandre M. Bayen, Peter L. Bartlett		code	-1
Sub-sampled Newton Methods with Non-uniform Sampling	Peng Xu, Jiyan Yang, Farbod RoostaKhorasani, Christopher Ré, Michael W. Mahoney		code	-1
Stochastic Gradient Geodesic MCMC Methods	Chang Liu, Jun Zhu, Yang Song		code	-1
Variational Bayes on Monte Carlo Steroids	Aditya Grover, Stefano Ermon		code	-1
Showing versus doing: Teaching by demonstration	Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil		code	-1
Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation	Jianxu Chen, Lin Yang, Yizhe Zhang, Mark S. Alber, Danny Ziyi Chen		code	-1
Maximization of Approximately Submodular Functions	Thibaut Horel, Yaron Singer		code	-1
A Comprehensive Linear Speedup Analysis for Asynchronous Stochastic Parallel Optimization from Zeroth-Order to First-Order	Xiangru Lian, Huan Zhang, ChoJui Hsieh, Yijun Huang, Ji Liu		code	-1
Learning Infinite RBMs with Frank-Wolfe	Wei Ping, Qiang Liu, Alexander Ihler		code	-1
Estimating the Size of a Large Network and its Communities from a Random Sample	Lin Chen, Amin Karbasi, Forrest W. Crawford		code	-1
Learning Sensor Multiplexing Design through Back-propagation	Ayan Chakrabarti		code	-1
On Robustness of Kernel Clustering	Bowei Yan, Purnamrita Sarkar		code	-1
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression	Kameron Decker Harris, Stefan Mihalas, Eric SheaBrown		code	-1
MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild	Grégory Rogez, Cordelia Schmid		code	-1
New Liftable Classes for First-Order Probabilistic Inference	Seyed Mehran Kazemi, Angelika Kimmig, Guy Van den Broeck, David Poole		code	-1
The Parallel Knowledge Gradient Method for Batch Bayesian Optimization	Jian Wu, Peter I. Frazier		code	-1
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits	Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire		code	-1
Consistent Estimation of Functions of Data Missing Non-Monotonically and Not at Random	Ilya Shpitser		code	-1
Optimistic Gittins Indices	Eli Gutin, Vivek F. Farias		code	-1
Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models	Juho Lee, Lancelot F. James, Seungjin Choi		code	-1
Launch and Iterate: Reducing Prediction Churn	Mahdi Milani Fard, Quentin Cormier, Kevin Robert Canini, Maya R. Gupta		code	-1
"Congruent" and "Opposite" Neurons: Sisters for Multisensory Integration and Segregation	Wenhao Zhang, He Wang, K. Y. Michael Wong, Si Wu		code	-1
Learning shape correspondence with anisotropic convolutional neural networks	Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein		code	-1
Pairwise Choice Markov Chains	Stephen Ragain, Johan Ugander		code	-1
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization	Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang		code	-1
Clustering with Same-Cluster Queries	Hassan Ashtiani, Shrinu Kushagra, Shai BenDavid		code	-1
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models	S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton		code	-1
Parameter Learning for Log-supermodular Distributions	Tatiana Shpakova, Francis R. Bach		code	-1
Deconvolving Feedback Loops in Recommender Systems	Ayan Sinha, David F. Gleich, Karthik Ramani		code	-1
Structured Matrix Recovery via the Generalized Dantzig Selector	Sheng Chen, Arindam Banerjee		code	-1
Confusions over Time: An Interpretable Bayesian Model to Characterize Trends in Decision Making	Himabindu Lakkaraju, Jure Leskovec		code	-1
Automatic Neuron Detection in Calcium Imaging Data Using Convolutional Networks	Noah J. Apthorpe, Alexander J. Riordan, Rob E. Aguilar, Jan Homann, Yi Gu, David W. Tank, H. Sebastian Seung		code	-1
Designing smoothing functions for improved worst-case competitive ratio in online optimization	Reza Eghbali, Maryam Fazel		code	-1
Convergence guarantees for kernel-based quadrature rules in misspecified settings	Motonobu Kanagawa, Bharath K. Sriperumbudur, Kenji Fukumizu		code	-1
Unsupervised Learning from Noisy Networks with Applications to Hi-C Data	Bo Wang, Junjie Zhu, Armin Pourshafeie, Oana Ursu, Serafim Batzoglou, Anshul Kundaje		code	-1
A Non-generative Framework and Convex Relaxations for Unsupervised Learning	Elad Hazan, Tengyu Ma		code	-1
Equality of Opportunity in Supervised Learning	Moritz Hardt, Eric Price, Nati Srebro		code	-1
Scaled Least Squares Estimator for GLMs in Large-Scale Problems	Murat A. Erdogdu, Lee H. Dicker, Mohsen Bayati		code	-1
Interpretable Nonlinear Dynamic Modeling of Neural Trajectories	Yuan Zhao, Il Memming Park		code	-1
Search Improves Label for Active Learning	Alina Beygelzimer, Daniel J. Hsu, John Langford, Chicheng Zhang		code	-1
Higher-Order Factorization Machines	Mathieu Blondel, Akinori Fujino, Naonori Ueda, Masakazu Ishihata		code	-1
Exponential expressivity in deep neural networks through transient chaos	Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha SohlDickstein, Surya Ganguli		code	-1
Split LBI: An Iterative Regularization Path with Structural Sparsity	Chendi Huang, Xinwei Sun, Jiechao Xiong, Yuan Yao		code	-1
An equivalence between high dimensional Bayes optimal inference and M-estimation	Madhu Advani, Surya Ganguli		code	-1
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks	Anh Mai Nguyen, Alexey Dosovitskiy, Jason Yosinski, Thomas Brox, Jeff Clune		code	-1
Deep Submodular Functions: Definitions and Learning	Brian W. Dolhansky, Jeff A. Bilmes		code	-1
Discriminative Gaifman Models	Mathias Niepert		code	-1
Leveraging Sparsity for Efficient Submodular Data Summarization	Erik M. Lindgren, Shanshan Wu, Alexandros G. Dimakis		code	-1
Local Minimax Complexity of Stochastic Convex Optimization	Sabyasachi Chatterjee, John C. Duchi, John D. Lafferty, Yuancheng Zhu		code	-1
Stochastic Optimization for Large-scale Optimal Transport	Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach		code	-1
On Mixtures of Markov Chains	Rishi Gupta, Ravi Kumar, Sergei Vassilvitskii		code	-1
Linear Contextual Bandits with Knapsacks	Shipra Agrawal, Nikhil R. Devanur		code	-1
Reconstructing Parameters of Spreading Models from Partial Observations	Andrey Y. Lokhov		code	-1
Spatiotemporal Residual Networks for Video Action Recognition	Christoph Feichtenhofer, Axel Pinz, Richard P. Wildes		code	-1
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations	Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro		code	-1
Strategic Attentive Writer for Learning Macro-Actions	Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John P. Agapiou, Koray Kavukcuoglu		code	-1
The Limits of Learning with Missing Data	Brian Bullins, Elad Hazan, Tomer Koren		code	-1
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism	Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, Walter F. Stewart		code	-1
Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers	Veeranjaneyulu Sadhanala, YuXiang Wang, Ryan J. Tibshirani		code	-1
Community Detection on Evolving Graphs	Aris Anagnostopoulos, Jakub Lacki, Silvio Lattanzi, Stefano Leonardi, Mohammad Mahdian		code	-1
Online and Differentially-Private Tensor Decomposition	Yining Wang, Anima Anandkumar		code	-1
Dimension-Free Iteration Complexity of Finite Sum Optimization Problems	Yossi Arjevani, Ohad Shamir		code	-1
Towards Conceptual Compression	Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra		code	-1
Exact Recovery of Hard Thresholding Pursuit	XiaoTong Yuan, Ping Li, Tong Zhang		code	-1
Data Programming: Creating Large Training Sets, Quickly	Alexander J. Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré		code	-1
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back	Vitaly Feldman		code	-1
Dynamic matrix recovery from incomplete observations under an exact low-rank constraint	Liangbei Xu, Mark A. Davenport		code	-1
Fast Distributed Submodular Cover: Public-Private Data Summarization	Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi		code	-1
Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods	Cristina Savin, Gasper Tkacik		code	-1
Lifelong Learning with Weighted Majority Votes	Anastasia Pentina, Ruth Urner		code	-1
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes	Jack W. Rae, Jonathan J. Hunt, Ivo Danihelka, Timothy Harley, Andrew W. Senior, Gregory Wayne, Alex Graves, Tim Lillicrap		code	-1
Matching Networks for One Shot Learning	Oriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, Daan Wierstra		code	-1
Tight Complexity Bounds for Optimizing Composite Objectives	Blake E. Woodworth, Nati Srebro		code	-1
Graphical Time Warping for Joint Alignment of Multiple Curves	Yizhi Wang, David J. Miller, Kira Poskanzer, Yue Wang, Lin Tian, Guoqiang Yu		code	-1
Unsupervised Risk Estimation Using Only Conditional Independence Structure	Jacob Steinhardt, Percy Liang		code	-1
MetaGrad: Multiple Learning Rates in Online Learning	Tim van Erven, Wouter M. Koolen		code	-1
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation	Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum		code	-1
High Dimensional Structured Superposition Models	Qilong Gu, Arindam Banerjee		code	-1
Joint quantile regression in vector-valued RKHSs	Maxime Sangnier, Olivier Fercoq, Florence d'AlchéBuc		code	-1
The Forget-me-not Process	Kieran Milan, Joel Veness, James Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis		code	-1
Wasserstein Training of Restricted Boltzmann Machines	Grégoire Montavon, KlausRobert Müller, Marco Cuturi		code	-1
Communication-Optimal Distributed Clustering	Jiecao Chen, He Sun, David P. Woodruff, Qin Zhang		code	-1
Probing the Compositionality of Intuitive Functions	Eric Schulz, Josh Tenenbaum, David Duvenaud, Maarten Speekenbrink, Samuel J. Gershman		code	-1
Ladder Variational Autoencoders	Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther		code	-1
The Multiple Quantile Graphical Model	Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani		code	-1
Threshold Learning for Optimal Decision Making	Nathan F. Lepora		code	-1
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA	Aapo Hyvärinen, Hiroshi Morioka		code	-1
Can Active Memory Replace Attention?	Lukasz Kaiser, Samy Bengio		code	-1
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning	Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami		code	-1
The Product Cut	Thomas Laurent, James H. von Brecht, Xavier Bresson, Arthur Szlam		code	-1
Learning Sparse Gaussian Graphical Models with Overlapping Blocks	Mohammad Javad Hosseini, SuIn Lee		code	-1
Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale	Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet Talwalkar		code	-1
Average-case hardness of RIP certification	Tengyao Wang, Quentin Berthet, Yaniv Plan		code	-1
A forward model at Purkinje cell synapses facilitates cerebellar anticipatory control	Ivan Herreros, Xerxes D. Arsiwalla, Paul F. M. J. Verschure		code	-1
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	Michaël Defferrard, Xavier Bresson, Pierre Vandergheynst		code	-1
CliqueCNN: Deep Unsupervised Exemplar Learning	Miguel Ángel Bautista, Artsiom Sanakoyeu, Ekaterina Tikhoncheva, Björn Ommer		code	-1
Large-Scale Price Optimization via Network Flow	Shinji Ito, Ryohei Fujimaki		code	-1
Online Pricing with Strategic and Patient Buyers	Michal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar		code	-1
Global Optimality of Local Search for Low Rank Matrix Recovery	Srinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro		code	-1
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences	Daniel Neil, Michael Pfeiffer, ShihChii Liu		code	-1
Improving PAC Exploration Using the Median Of Means	Jason Pazis, Ronald Parr, Jonathan P. How		code	-1
Infinite Hidden Semi-Markov Modulated Interaction Point Process	Peng Lin, Bang Zhang, Ting Guo, Yang Wang, Fang Chen		code	-1
Cooperative Inverse Reinforcement Learning	Dylan HadfieldMenell, Stuart Russell, Pieter Abbeel, Anca D. Dragan		code	-1
Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments	Ransalu Senanayake, Lionel Ott, Simon Timothy O'Callaghan, Fabio Tozeto Ramos		code	-1
Select-and-Sample for Spike-and-Slab Sparse Coding	AbdulSaboor Sheikh, Jörg Lücke		code	-1
Tractable Operations for Arithmetic Circuits of Probabilistic Models	Yujia Shen, Arthur Choi, Adnan Darwiche		code	-1
Greedy Feature Construction	Dino Oglic, Thomas Gärtner		code	-1
Mistake Bounds for Binary Matrix Completion	Mark Herbster, Stephen Pasteris, Massimiliano Pontil		code	-1
Data driven estimation of Laplace-Beltrami operator	Frédéric Chazal, Ilaria Giulini, Bertrand Michel		code	-1
Tracking the Best Expert in Non-stationary Stochastic Environments	ChenYu Wei, YiTe Hong, ChiJen Lu		code	-1
Learning to learn by gradient descent by gradient descent	Marcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas		code	-1
Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes	Hassan A. Kingravi, Harshal R. Maske, Girish Chowdhary		code	-1
Quantum Perceptron Models	Ashish Kapoor, Nathan Wiebe, Krysta M. Svore		code	-1
Guided Policy Search via Approximate Mirror Descent	William H. Montgomery, Sergey Levine		code	-1
The Power of Optimization from Samples	Eric Balkanski, Aviad Rubinstein, Yaron Singer		code	-1
Deep Exploration via Bootstrapped DQN	Ian Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy		code	-1
A Multi-step Inertial Forward-Backward Splitting Method for Non-convex Optimization	Jingwei Liang, Jalal Fadili, Gabriel Peyré		code	-1
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages	Yin Cheng Ng, Pawel M. Chilinski, Ricardo Silva		code	-1
Convolutional Neural Fabrics	Shreyas Saxena, Jakob Verbeek		code	-1
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy	Aryan Mokhtari, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann, Alejandro Ribeiro		code	-1
A Sparse Interactive Model for Matrix Completion with Side Information	Jin Lu, Guannan Liang, Jiangwen Sun, Jinbo Bi		code	-1
Coresets for Scalable Bayesian Logistic Regression	Jonathan H. Huggins, Trevor Campbell, Tamara Broderick		code	-1
Agnostic Estimation for Misspecified Phase Retrieval Models	Matey Neykov, Zhaoran Wang, Han Liu		code	-1
Linear Relaxations for Finding Diverse Elements in Metric Spaces	Aditya Bhaskara, Mehrdad Ghadiri, Vahab S. Mirrokni, Ola Svensson		code	-1
Binarized Neural Networks	Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran ElYaniv, Yoshua Bengio		code	-1
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences	Chi Jin, Yuchen Zhang, Sivaraman Balakrishnan, Martin J. Wainwright, Michael I. Jordan		code	-1
Memory-Efficient Backpropagation Through Time	Audrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves		code	-1
Bayesian Optimization with Robust Bayesian Neural Networks	Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter		code	-1
Learnable Visual Markers	Oleg Grinchuk, Vadim Lebedev, Victor S. Lempitsky		code	-1
Fast Algorithms for Robust PCA via Gradient Descent	Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis		code	-1
One-vs-Each Approximation to Softmax for Scalable Estimation of Probabilities	Michalis K. Titsias		code	-1
Learning Deep Embeddings with Histogram Loss	Evgeniya Ustinova, Victor S. Lempitsky		code	-1
Spectral Learning of Dynamic Systems from Nonequilibrium Data	Hao Wu, Frank Noé		code	-1
Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling	Chengtao Li, Suvrit Sra, Stefanie Jegelka		code	-1
Mapping Estimation for Discrete Optimal Transport	Michaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard		code	-1
Batched Gaussian Process Bandit Optimization via Determinantal Point Processes	Tarun Kathuria, Amit Deshpande, Pushmeet Kohli		code	-1
Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images	Vladimir Golkov, Marcin J. Skwark, Antonij Golkov, Alexey Dosovitskiy, Thomas Brox, Jens Meiler, Daniel Cremers		code	-1
Linear Feature Encoding for Reinforcement Learning	Zhao Song, Ronald E. Parr, Xuejun Liao, Lawrence Carin		code	-1
A Minimax Approach to Supervised Learning	Farzan Farnia, David Tse		code	-1
Edge-exchangeable graphs and sparsity	Diana Cai, Trevor Campbell, Tamara Broderick		code	-1
A Locally Adaptive Normal Distribution	Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg		code	-1
Completely random measures for modelling block-structured sparse networks	Tue Herlau, Mikkel N. Schmidt, Morten Mørup		code	-1
Sparse Support Recovery with Non-smooth Loss Functions	Kévin Degraux, Gabriel Peyré, Jalal Fadili, Laurent Jacques		code	-1
Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics	Travis Monk, Cristina Savin, Jörg Lücke		code	-1
Learning values across many orders of magnitude	Hado van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver		code	-1
Adaptive Smoothed Online Multi-Task Learning	Keerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang		code	-1
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes	Matteo Turchetta, Felix Berkenkamp, Andreas Krause		code	-1
Probabilistic Linear Multistep Methods	Onur Teymur, Konstantinos Zygalakis, Ben Calderhead		code	-1
Stochastic Three-Composite Convex Minimization	Alp Yurtsever, Bang Công Vu, Volkan Cevher		code	-1
Using Fast Weights to Attend to the Recent Past	Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu		code	-1
Maximal Sparsity with Deep Networks?	Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf, Baoyuan Wang		code	-1
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings	Tolga Bolukbasi, KaiWei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai		code	-1
beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data	Valentina Zantedeschi, Rémi Emonet, Marc Sebban		code	-1
Learning Additive Exponential Family Graphical Models via \ell_{2, 1}-norm Regularized M-Estimation	XiaoTong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu		code	-1
Backprop KF: Learning Discriminative Deterministic State Estimators	Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel		code	-1
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks	Xiang Li, Tao Qin, Jian Yang, TieYan Liu		code	-1
Fast recovery from a union of subspaces	Chinmay Hegde, Piotr Indyk, Ludwig Schmidt		code	-1
Incremental Variational Sparse Gaussian Process Regression	ChingAn Cheng, Byron Boots		code	-1
A Consistent Regularization Approach for Structured Prediction	Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi		code	-1
Clustering Signed Networks with the Geometric Mean of Laplacians	Pedro Mercado, Francesco Tudisco, Matthias Hein		code	-1
An urn model for majority voting in classification ensembles	Víctor Soto, Alberto Suárez, Gonzalo MartínezMuñoz		code	-1
Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer Prediction	Jacob Steinhardt, Gregory Valiant, Moses Charikar		code	-1
Fast and accurate spike sorting of high-channel count probes with KiloSort	Marius Pachitariu, Nicholas A. Steinmetz, Shabnam N. Kadir, Matteo Carandini, Kenneth D. Harris		code	-1
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning	Wouter M. Koolen, Peter Grünwald, Tim van Erven		code	-1
Ancestral Causal Inference	Sara Magliacane, Tom Claassen, Joris M. Mooij		code	-1
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning	Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu		code	-1
Tagger: Deep Unsupervised Perceptual Grouping	Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber		code	-1
An Efficient Streaming Algorithm for the Submodular Cover Problem	Ashkan NorouziFard, Abbas Bazzi, Ilija Bogunovic, Marwa El Halabi, YaPing Hsieh, Volkan Cevher		code	-1
Interaction Networks for Learning about Objects, Relations and Physics	Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, Koray Kavukcuoglu		code	-1
Efficient state-space modularization for planning: theory, behavioral and neural signatures	Daniel McNamee, Daniel M. Wolpert, Máté Lengyel		code	-1
Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient Descent	Chi Jin, Sham M. Kakade, Praneeth Netrapalli		code	-1
Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics	WeiShou Hsu, Pascal Poupart		code	-1
Computing and maximizing influence in linear threshold and triggering models	Justin T. Khim, Varun S. Jog, PoLing Loh		code	-1
Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions	Yichen Wang, Nan Du, Rakshit Trivedi, Le Song		code	-1
Optimal Learning for Multi-pass Stochastic Gradient Methods	Junhong Lin, Lorenzo Rosasco		code	-1
Generative Adversarial Imitation Learning	Jonathan Ho, Stefano Ermon		code	-1
Latent Attention For If-Then Program Synthesis	Chang Liu, Xinyun Chen, Eui Chul Richard Shin, Mingcheng Chen, Dawn Xiaodong Song		code	-1
Dual Space Gradient Descent for Online Learning	Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung		code	-1
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds	Hongyi Zhang, Sashank J. Reddi, Suvrit Sra		code	-1
Professor Forcing: A New Algorithm for Training Recurrent Networks	Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio		code	-1
Learning brain regions via large-scale online structured sparse dictionary learning	Elvis Dohmatob, Arthur Mensch, Gaël Varoquaux, Bertrand Thirion		code	-1
Efficient Neural Codes under Metabolic Constraints	Zhuo Wang, XueXin Wei, Alan A. Stocker, Daniel D. Lee		code	-1
Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods	Andrej Risteski, Yuanzhi Li		code	-1
Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information	Alexander Shishkin, Anastasia A. Bezzubtseva, Alexey Drutsa, Ilia Shishkov, Ekaterina Gladkikh, Gleb Gusev, Pavel Serdyukov		code	-1
Bayesian Intermittent Demand Forecasting for Large Inventories	Matthias W. Seeger, David Salinas, Valentin Flunkert		code	-1
Visual Question Answering with Question Representation Update (QRU)	Ruiyu Li, Jiaya Jia		code	-1
Learning Parametric Sparse Models for Image Super-Resolution	Yongbo Li, Weisheng Dong, Xuemei Xie, Guangming Shi, Xin Li, Donglai Xu		code	-1
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning	JeanBastien Grill, Michal Valko, Rémi Munos		code	-1
Asynchronous Parallel Greedy Coordinate Descent	Yang You, Xiangru Lian, Ji Liu, HsiangFu Yu, Inderjit S. Dhillon, James Demmel, ChoJui Hsieh		code	-1
Iterative Refinement of the Approximate Posterior for Directed Belief Networks	R. Devon Hjelm, Russ Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince D. Calhoun, Junyoung Chung		code	-1
Assortment Optimization Under the Mallows model	Antoine Désir, Vineet Goyal, Srikanth Jagabathula, Danny Segev		code	-1
Disease Trajectory Maps	Peter Schulam, Raman Arora		code	-1
Multistage Campaigning in Social Networks	Mehrdad Farajtabar, Xiaojing Ye, Sahar Harati, Le Song, Hongyuan Zha		code	-1
Learning in Games: Robustness of Fast Convergence	Dylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos		code	-1
Improving Variational Autoencoders with Inverse Autoregressive Flow	Diederik P. Kingma, Tim Salimans, Rafal Józefowicz, Xi Chen, Ilya Sutskever, Max Welling		code	-1
Algorithms and matching lower bounds for approximately-convex optimization	Andrej Risteski, Yuanzhi Li		code	-1
Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization	Tyler B. Johnson, Carlos Guestrin		code	-1
Kernel Bayesian Inference with Posterior Regularization	Yang Song, Jun Zhu, Yong Ren		code	-1
Neural Universal Discrete Denoiser	Taesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon		code	-1
Optimal Architectures in a Solvable Model of Deep Networks	Jonathan Kadmon, Haim Sompolinsky		code	-1
Conditional Image Generation with PixelCNN Decoders	Aäron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Koray Kavukcuoglu, Oriol Vinyals, Alex Graves		code	-1
Supervised Learning with Tensor Networks	Edwin Miles Stoudenmire, David J. Schwab		code	-1
Multi-step learning and underlying structure in statistical models	Maia Fraser		code	-1
Structure-Blind Signal Recovery	Dmitry Ostrovsky, Zaïd Harchaoui, Anatoli B. Juditsky, Arkadi Nemirovski		code	-1
An Architecture for Deep, Hierarchical Generative Models	Philip Bachman		code	-1
Feature selection in functional data classification with recursive maxima hunting	José L. Torrecilla, Alberto Suárez		code	-1
Achieving budget-optimality with adaptive schemes in crowdsourcing	Ashish Khetan, Sewoong Oh		code	-1
Near-Optimal Smoothing of Structured Conditional Probability Matrices	Moein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky		code	-1
Supervised Word Mover's Distance	Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger		code	-1
Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models	Amin Jalali, Qiyang Han, Ioana Dumitriu, Maryam Fazel		code	-1
Full-Capacity Unitary Recurrent Neural Networks	Scott Wisdom, Thomas Powers, John R. Hershey, Jonathan Le Roux, Les E. Atlas		code	-1
Threshold Bandits, With and Without Censored Feedback	Jacob D. Abernethy, Kareem Amin, Ruihao Zhu		code	-1
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks	Wenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel		code	-1
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods	Lev Bogolubsky, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gleb Gusev, Yurii E. Nesterov, Andrei M. Raigorodskii, Aleksey Tikhonov, Maksim Zhukovskii		code	-1
k*-Nearest Neighbors: From Global to Local	Oren Anava, Kfir Y. Levy		code	-1
Normalized Spectral Map Synchronization	Yanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi		code	-1
Beyond Exchangeability: The Chinese Voting Process	Moontae Lee, Seok Hyun Jin, David M. Mimno		code	-1
A posteriori error bounds for joint matrix decomposition problems	Nicolò Colombo, Nikos Vlassis		code	-1
A Bayesian method for reducing bias in neural representational similarity analysis	Mingbo Cai, Nicolas W. Schuck, Jonathan W. Pillow, Yael Niv		code	-1
Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes	Chris Junchi Li, Zhaoran Wang, Han Liu		code	-1
Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities	Ruitong Huang, Tor Lattimore, András György, Csaba Szepesvári		code	-1
SDP Relaxation with Randomized Rounding for Energy Disaggregation	Kiarash Shaloudegi, András György, Csaba Szepesvári, Wilsun Xu		code	-1
Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates	Yuanzhi Li, Yingyu Liang, Andrej Risteski		code	-1
Unsupervised Learning of 3D Structure from Images	Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter W. Battaglia, Max Jaderberg, Nicolas Heess		code	-1
Poisson-Gamma dynamical systems	Aaron Schein, Hanna M. Wallach, Mingyuan Zhou		code	-1
Gaussian Processes for Survival Analysis	Tamara Fernandez, Nicolas Rivera, Yee Whye Teh		code	-1
Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain	Ian EnHsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep Ravikumar, Inderjit S. Dhillon		code	-1
Optimal Binary Classifier Aggregation for General Losses	Akshay Balsubramani, Yoav Freund		code	-1
Disentangling factors of variation in deep representation using adversarial training	Michaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun		code	-1
A primal-dual method for conic constrained distributed optimization problems	Necdet Serhat Aybat, Erfan Yazdandoost Hamedani		code	-1
Fundamental Limits of Budget-Fidelity Trade-off in Label Crowdsourcing	Farshad Lahouti, Babak Hassibi		code	-1
An Online Sequence-to-Sequence Model Using Partial Conditioning	Navdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio		code	-1
Learning Deep Parsimonious Representations	Renjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun		code	-1
Cyclades: Conflict-free Asynchronous Machine Learning			code	-1
Learning to Poke by Poking: Experiential Learning of Intuitive Physics			code	-1
Only H is left: Near-tight Episodic PAC RL			code	-1