nips2015.md

NIPS2015 Paper List

论文	作者	摘要	代码	引用数
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing	Nihar Bhadresh Shah, Denny Zhou		code	-1
Learning with Symmetric Label Noise: The Importance of Being Unhinged	Brendan van Rooyen, Aditya Krishna Menon, Robert C. Williamson		code	-1
Algorithmic Stability and Uniform Generalization	Ibrahim M. Alabdulmohsin		code	-1
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models	Theodoros Tsiligkaridis, Keith W. Forsythe		code	-1
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling	Xiaocheng Shang, Zhanxing Zhu, Benedict J. Leimkuhler, Amos J. Storkey		code	-1
Robust Portfolio Optimization	Huitong Qiu, Fang Han, Han Liu, Brian Caffo		code	-1
Logarithmic Time Online Multiclass prediction	Anna Choromanska, John Langford		code	-1
Planar Ultrametrics for Image Segmentation	Julian Yarkony, Charless C. Fowlkes		code	-1
Expressing an Image Stream with a Sequence of Natural Sentences	Cesc C. Park, Gunhee Kim		code	-1
Parallel Correlation Clustering on Big Graphs	Xinghao Pan, Dimitris S. Papailiopoulos, Samet Oymak, Benjamin Recht, Kannan Ramchandran, Michael I. Jordan		code	-1
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	Shaoqing Ren, Kaiming He, Ross B. Girshick, Jian Sun		code	-1
Space-Time Local Embeddings	Ke Sun, Jun Wang, Alexandros Kalousis, Stéphane MarchandMaillet		code	-1
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements	Qinqing Zheng, John D. Lafferty		code	-1
Smooth Interactive Submodular Set Cover	Bryan D. He, Yisong Yue		code	-1
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning	Jiajun Wu, Ilker Yildirim, Joseph J. Lim, Bill Freeman, Joshua B. Tenenbaum		code	-1
On the Pseudo-Dimension of Nearly Optimal Auctions	Jamie Morgenstern, Tim Roughgarden		code	-1
Unlocking neural population non-stationarities using hierarchical dynamics models	Mijung Park, Gergo Bohner, Jakob H. Macke		code	-1
Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM)	Mijung Park, Wittawat Jitkrittum, Ahmad Qamar, Zoltán Szabó, Lars Buesing, Maneesh Sahani		code	-1
Color Constancy by Learning to Predict Chromaticity from Luminance	Ayan Chakrabarti		code	-1
Fast and Accurate Inference of Plackett-Luce Models	Lucas Maystre, Matthias Grossglauser		code	-1
Probabilistic Line Searches for Stochastic Optimization	Maren Mahsereci, Philipp Hennig		code	-1
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets	Armand Joulin, Tomás Mikolov		code	-1
Where are they looking?	Adrià Recasens, Aditya Khosla, Carl Vondrick, Antonio Torralba		code	-1
The Pareto Regret Frontier for Bandits	Tor Lattimore		code	-1
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors	Andrea Montanari, Daniel Reichman, Ofer Zeitouni		code	-1
Measuring Sample Quality with Stein's Method	Jackson Gorham, Lester W. Mackey		code	-1
Bidirectional Recurrent Convolutional Networks for Multi-Frame Super-Resolution	Yan Huang, Wei Wang, Liang Wang		code	-1
Bounding errors of Expectation-Propagation	Guillaume P. Dehaene, Simon Barthelmé		code	-1
A fast, universal algorithm to learn parametric nonlinear embeddings	Miguel Á. CarreiraPerpiñán, Max Vladymyrov		code	-1
Texture Synthesis Using Convolutional Neural Networks	Leon A. Gatys, Alexander S. Ecker, Matthias Bethge		code	-1
Extending Gossip Algorithms to Distributed Estimation of U-statistics	Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon		code	-1
Streaming, Distributed Variational Inference for Bayesian Nonparametrics	Trevor Campbell, Julian Straub, John W. Fisher III, Jonathan P. How		code	-1
Learning visual biases from human imagination	Carl Vondrick, Hamed Pirsiavash, Aude Oliva, Antonio Torralba		code	-1
Smooth and Strong: MAP Inference with Linear Convergence	Ofer Meshi, Mehrdad Mahdavi, Alexander G. Schwing		code	-1
Copeland Dueling Bandits	Masrour Zoghi, Zohar S. Karnin, Shimon Whiteson, Maarten de Rijke		code	-1
Optimal Ridge Detection using Coverage Risk	YenChi Chen, Christopher R. Genovese, Shirley Ho, Larry A. Wasserman		code	-1
Top-k Multiclass SVM	Maksim Lapin, Matthias Hein, Bernt Schiele		code	-1
Policy Evaluation Using the Ω-Return	Philip S. Thomas, Scott Niekum, Georgios Theocharous, George Dimitri Konidaris		code	-1
Orthogonal NMF through Subspace Exploration	Megasthenis Asteris, Dimitris S. Papailiopoulos, Alexandros G. Dimakis		code	-1
Stochastic Online Greedy Learning with Semi-bandit Feedbacks	Tian Lin, Jian Li, Wei Chen		code	-1
Deeply Learning the Messages in Message Passing Inference	Guosheng Lin, Chunhua Shen, Ian D. Reid, Anton van den Hengel		code	-1
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring	David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass		code	-1
Accelerated Proximal Gradient Methods for Nonconvex Programming	Huan Li, Zhouchen Lin		code	-1
Approximating Sparse PCA from Incomplete Data	Abhisek Kundu, Petros Drineas, Malik MagdonIsmail		code	-1
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations	Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, Larry A. Wasserman, James M. Robins		code	-1
Column Selection via Adaptive Sampling	Saurabh Paul, Malik MagdonIsmail, Petros Drineas		code	-1
HONOR: Hybrid Optimization for NOn-convex Regularized problems	Pinghua Gong, Jieping Ye		code	-1
3D Object Proposals for Accurate Object Class Detection	Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G. Berneshawi, Huimin Ma, Sanja Fidler, Raquel Urtasun		code	-1
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits	Huasen Wu, R. Srikant, Xin Liu, Chong Jiang		code	-1
Tensorizing Neural Networks	Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov		code	-1
Parallelizing MCMC with Random Partition Trees	Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson		code	-1
A Reduced-Dimension fMRI Shared Response Model	PoHsuan Chen, Janice Chen, Yaara Yeshurun, Uri Hasson, James V. Haxby, Peter J. Ramadge		code	-1
Spectral Learning of Large Structured HMMs for Comparative Epigenomics	Chicheng Zhang, Jimin Song, Kamalika Chaudhuri, Kevin C. Chen		code	-1
Individual Planning in Infinite-Horizon Multiagent Settings: Inference, Structure and Scalability	Xia Qu, Prashant Doshi		code	-1
Estimating Mixture Models via Mixtures of Polynomials	Sida Wang, Arun Tejasvi Chaganty, Percy Liang		code	-1
On the Global Linear Convergence of Frank-Wolfe Optimization Variants	Simon LacosteJulien, Martin Jaggi		code	-1
Deep Knowledge Tracing	Chris Piech, Jonathan Bassen, Jonathan Huang, Surya Ganguli, Mehran Sahami, Leonidas J. Guibas, Jascha SohlDickstein		code	-1
Rethinking LDA: Moment Matching for Discrete ICA	Anastasia Podosinnikova, Francis R. Bach, Simon LacosteJulien		code	-1
Efficient Compressive Phase Retrieval with Constrained Sensing Vectors	Sohail Bahmani, Justin K. Romberg		code	-1
Barrier Frank-Wolfe for Marginal Inference	Rahul G. Krishnan, Simon LacosteJulien, David A. Sontag		code	-1
Learning Theory and Algorithms for Forecasting Non-stationary Time Series	Vitaly Kuznetsov, Mehryar Mohri		code	-1
Compressive spectral embedding: sidestepping the SVD	Dinesh Ramasamy, Upamanyu Madhow		code	-1
A Nonconvex Optimization Framework for Low Rank Matrix Estimation	Tuo Zhao, Zhaoran Wang, Han Liu		code	-1
Automatic Variational Inference in Stan	Alp Kucukelbir, Rajesh Ranganath, Andrew Gelman, David M. Blei		code	-1
Attention-Based Models for Speech Recognition	Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio		code	-1
Closed-form Estimators for High-dimensional Generalized Linear Models	Eunho Yang, Aurélie C. Lozano, Pradeep Ravikumar		code	-1
Online F-Measure Optimization	Róbert BusaFekete, Balázs Szörényi, Krzysztof Dembczynski, Eyke Hüllermeier		code	-1
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach	Balázs Szörényi, Róbert BusaFekete, Adil Paul, Eyke Hüllermeier		code	-1
M-Best-Diverse Labelings for Submodular Energies and Beyond	Alexander Kirillov, Dmytro Shlezinger, Dmitry P. Vetrov, Carsten Rother, Bogdan Savchynskyy		code	-1
Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number	Janne H. Korhonen, Pekka Parviainen		code	-1
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring	Gunwoong Park, Garvesh Raskutti		code	-1
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy	Marylou Gabrié, Eric W. Tramel, Florent Krzakala		code	-1
Character-level Convolutional Networks for Text Classification	Xiang Zhang, Junbo Jake Zhao, Yann LeCun		code	-1
Robust Feature-Sample Linear Discriminant Analysis for Brain Disorders Diagnosis	Ehsan AdeliMosabbeb, KimHan Thung, Le An, Feng Shi, Dinggang Shen		code	-1
Black-box optimization of noisy functions with unknown smoothness	JeanBastien Grill, Michal Valko, Rémi Munos		code	-1
Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters	Emmanuel Abbe, Colin Sandon		code	-1
Deep learning with Elastic Averaging SGD	Sixin Zhang, Anna Choromanska, Yann LeCun		code	-1
Monotone k-Submodular Function Maximization with Size Constraints	Naoto Ohsaka, Yuichi Yoshida		code	-1
Active Learning from Weak and Strong Labelers	Chicheng Zhang, Kamalika Chaudhuri		code	-1
On the Optimality of Classifier Chain for Multi-label Classification	Weiwei Liu, Ivor W. Tsang		code	-1
Robust Regression via Hard Thresholding	Kush Bhatia, Prateek Jain, Purushottam Kar		code	-1
Sparse Local Embeddings for Extreme Multi-label Classification	Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain		code	-1
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems	Yuxin Chen, Emmanuel J. Candès		code	-1
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure	Peter Schulam, Suchi Saria		code	-1
Subspace Clustering with Irrelevant Features via Robust Dantzig Selector	Chao Qu, Huan Xu		code	-1
Sparse PCA via Bipartite Matchings	Megasthenis Asteris, Dimitris S. Papailiopoulos, Anastasios Kyrillidis, Alexandros G. Dimakis		code	-1
Fast Randomized Kernel Ridge Regression with Statistical Guarantees	Ahmed El Alaoui, Michael W. Mahoney		code	-1
Online Learning for Adversaries with Memory: Price of Past Mistakes	Oren Anava, Elad Hazan, Shie Mannor		code	-1
Convolutional spike-triggered covariance analysis for neural subunit models	Anqi Wu, Il Memming Park, Jonathan W. Pillow		code	-1
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting	Xingjian Shi, Zhourong Chen, Hao Wang, DitYan Yeung, WaiKin Wong, Wangchun Woo		code	-1
GAP Safe screening rules for sparse multi-task and multi-class models	Eugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon		code	-1
Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces	Takashi Takenouchi, Takafumi Kanamori		code	-1
Statistical Model Criticism using Kernel Two Sample Tests	James Robert Lloyd, Zoubin Ghahramani		code	-1
Precision-Recall-Gain Curves: PR Analysis Done Right	Peter A. Flach, Meelis Kull		code	-1
A Generalization of Submodular Cover via the Diminishing Return Property on the Integer Lattice	Tasuku Soma, Yuichi Yoshida		code	-1
Bidirectional Recurrent Neural Networks as Generative Models	Mathias Berglund, Tapani Raiko, Mikko Honkala, Leo Kärkkäinen, Akos Vetek, Juha Karhunen		code	-1
Quartz: Randomized Dual Coordinate Ascent with Arbitrary Sampling	Zheng Qu, Peter Richtárik, Tong Zhang		code	-1
Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets	Justin Domke		code	-1
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks	Minhyung Cho, Chandra Shekhar Dhir, Jaehyung Lee		code	-1
Large-scale probabilistic predictors with and without guarantees of validity	Vladimir Vovk, Ivan Petej, Valentina Fedorova		code	-1
Shepard Convolutional Neural Networks	Jimmy S. J. Ren, Li Xu, Qiong Yan, Wenxiu Sun		code	-1
Matrix Manifold Optimization for Gaussian Mixtures	Reshad Hosseini, Suvrit Sra		code	-1
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding	Rie Johnson, Tong Zhang		code	-1
Parallel Recursive Best-First AND/OR Search for Exact MAP Inference in Graphical Models	Akihiro Kishimoto, Radu Marinescu, Adi Botea		code	-1
Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling	Ming Liang, Xiaolin Hu, Bo Zhang		code	-1
Bounding the Cost of Search-Based Lifted Inference	David B. Smith, Vibhav Gogate		code	-1
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families	Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltán Szabó, Arthur Gretton		code	-1
Linear Multi-Resource Allocation with Semi-Bandit Feedback	Tor Lattimore, Koby Crammer, Csaba Szepesvári		code	-1
Unsupervised Learning by Program Synthesis	Kevin Ellis, Armando SolarLezama, Joshua B. Tenenbaum		code	-1
Enforcing balance allows local supervised learning in spiking recurrent networks	Ralph Bourdoukan, Sophie Denève		code	-1
Fast and Guaranteed Tensor Decomposition via Sketching	Yining Wang, HsiaoYu Fish Tung, Alexander J. Smola, Anima Anandkumar		code	-1
Differentially private subspace clustering	Yining Wang, YuXiang Wang, Aarti Singh		code	-1
Predtron: A Family of Online Algorithms for General Prediction Problems	Prateek Jain, Nagarajan Natarajan, Ambuj Tewari		code	-1
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization	Fredrik D. Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt P. Dubhashi		code	-1
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk	Guillaume Papa, Stéphan Clémençon, Aurélien Bellet		code	-1
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs	Wei Cao, Jian Li, Yufei Tao, Zhize Li		code	-1
The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions	Sebastian Bitzer, Stefan J. Kiebel		code	-1
Fast Classification Rates for High-dimensional Gaussian Generative Models	Tianyang Li, Adarsh Prasad, Pradeep Ravikumar		code	-1
Fast Distributed k-Center Clustering with Outliers on Massive Data	Gustavo Malkomes, Matt J. Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley		code	-1
Human Memory Search as Initial-Visit Emitting Random Walk	KwangSung Jun, Xiaojin Zhu, Timothy T. Rogers, Zhuoran Yang, Ming Yuan		code	-1
Non-convex Statistical Optimization for Sparse Tensor Graphical Model	Wei Sun, Zhaoran Wang, Han Liu, Guang Cheng		code	-1
Convergence Rates of Active Learning for Maximum Likelihood Estimation	Kamalika Chaudhuri, Sham M. Kakade, Praneeth Netrapalli, Sujay Sanghavi		code	-1
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis	Jimei Yang, Scott E. Reed, MingHsuan Yang, Honglak Lee		code	-1
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets	Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier		code	-1
Backpropagation for Energy-Efficient Neuromorphic Computing	Steven K. Esser, Rathinakumar Appuswamy, Paul Merolla, John V. Arthur, Dharmendra S. Modha		code	-1
Alternating Minimization for Regression Problems with Vector-valued Outputs	Prateek Jain, Ambuj Tewari		code	-1
Learning both Weights and Connections for Efficient Neural Network	Song Han, Jeff Pool, John Tran, William J. Dally		code	-1
Optimal Rates for Random Fourier Features	Bharath K. Sriperumbudur, Zoltán Szabó		code	-1
The Population Posterior and Bayesian Modeling on Streams	James McInerney, Rajesh Ranganath, David M. Blei		code	-1
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees	FrançoisXavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne		code	-1
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks	Samy Bengio, Oriol Vinyals, Navdeep Jaitly, Noam Shazeer		code	-1
Unified View of Matrix Completion under General Structural Constraints	Suriya Gunasekar, Arindam Banerjee, Joydeep Ghosh		code	-1
Efficient Output Kernel Learning for Multiple Tasks	Pratik Jawanpuria, Maksim Lapin, Matthias Hein, Bernt Schiele		code	-1
Scalable Adaptation of State Complexity for Nonparametric Hidden Markov Models	Michael C. Hughes, William T. Stephenson, Erik B. Sudderth		code	-1
Variational Consensus Monte Carlo	Maxim Rabinovich, Elaine Angelino, Michael I. Jordan		code	-1
Newton-Stein Method: A Second Order Method for GLMs via Stein's Lemma	Murat A. Erdogdu		code	-1
Practical and Optimal LSH for Angular Distance	Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya P. Razenshteyn, Ludwig Schmidt		code	-1
Learning to Linearize Under Uncertainty	Ross Goroshin, Michaël Mathieu, Yann LeCun		code	-1
Finite-Time Analysis of Projected Langevin Monte Carlo	Sébastien Bubeck, Ronen Eldan, Joseph Lehec		code	-1
Deep Visual Analogy-Making	Scott E. Reed, Yi Zhang, Yuting Zhang, Honglak Lee		code	-1
Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation	Alaa Saade, Florent Krzakala, Lenka Zdeborová		code	-1
Online Learning with Adversarial Delays	Kent Quanrud, Daniel Khashabi		code	-1
Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection	Jie Wang, Jieping Ye		code	-1
Minimum Weight Perfect Matching via Blossom Belief Propagation	Sungsoo Ahn, Sejun Park, Michael Chertkov, Jinwoo Shin		code	-1
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation	Jaya Kawale, Hung Hai Bui, Branislav Kveton, Long TranThanh, Sanjay Chawla		code	-1
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems	Ruoyu Sun, Mingyi Hong		code	-1
Lifted Symmetry Detection and Breaking for MAP Inference	Timothy Kopp, Parag Singla, Henry A. Kautz		code	-1
Evaluating the statistical significance of biclusters	Jason D. Lee, Yuekai Sun, Jonathan E. Taylor		code	-1
Discriminative Robust Transformation Learning	Jiaji Huang, Qiang Qiu, Guillermo Sapiro, A. Robert Calderbank		code	-1
Bandits with Unobserved Confounders: A Causal Approach	Elias Bareinboim, Andrew Forney, Judea Pearl		code	-1
Scalable Semi-Supervised Aggregation of Classifiers	Akshay Balsubramani, Yoav Freund		code	-1
Online Learning with Gaussian Payoffs and Side Observations	Yifan Wu, András György, Csaba Szepesvári		code	-1
Private Graphon Estimation for Sparse Graphs	Christian Borgs, Jennifer T. Chayes, Adam D. Smith		code	-1
SubmodBoxes: Near-Optimal Search for a Set of Diverse Object Proposals	Qing Sun, Dhruv Batra		code	-1
Fast Second Order Stochastic Backpropagation for Variational Inference	Kai Fan, Ziteng Wang, Jeffrey M. Beck, James T. Kwok, Katherine A. Heller		code	-1
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition	Cameron Musco, Christopher Musco		code	-1
Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions	Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada, Takeshi Yamada		code	-1
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods	Amir Dezfouli, Edwin V. Bonilla		code	-1
Fast Bidirectional Probability Estimation in Markov Models	Siddhartha Banerjee, Peter Lofgren		code	-1
Probabilistic Variational Bounds for Graphical Models	Qiang Liu, John W. Fisher III, Alexander Ihler		code	-1
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes	Ryan Giordano, Tamara Broderick, Michael I. Jordan		code	-1
Combinatorial Cascading Bandits	Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvári		code	-1
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path	Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári		code	-1
Policy Gradient for Coherent Risk Measures	Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor		code	-1
Fast Rates for Exp-concave Empirical Risk Minimization	Tomer Koren, Kfir Y. Levy		code	-1
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks	Emily L. Denton, Soumith Chintala, Arthur Szlam, Rob Fergus		code	-1
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation	Seunghoon Hong, Hyeonwoo Noh, Bohyung Han		code	-1
Equilibrated adaptive learning rates for non-convex optimization	Yann N. Dauphin, Harm de Vries, Yoshua Bengio		code	-1
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions	Dominik Rothenhäusler, Christina Heinze, Jonas Peters, Nicolai Meinshausen		code	-1
Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach	Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone		code	-1
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care	Sorathan Chaturapruek, John C. Duchi, Christopher Ré		code	-1
Lifelong Learning with Non-i.i.d. Tasks	Anastasia Pentina, Christoph H. Lampert		code	-1
Optimal Linear Estimation under Unknown Nonlinear Transform	Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu		code	-1
Learning with Group Invariant Features: A Kernel Perspective	Youssef Mroueh, Stephen Voinea, Tomaso A. Poggio		code	-1
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees	Xinyang Yi, Constantine Caramanis		code	-1
Distributionally Robust Logistic Regression	Soroosh ShafieezadehAbadeh, Peyman Mohajerin Esfahani, Daniel Kuhn		code	-1
Adaptive Stochastic Optimization: From Sets to Paths	Zhan Wei Lim, David Hsu, Wee Sun Lee		code	-1
Beyond Convexity: Stochastic Quasi-Convex Optimization	Elad Hazan, Kfir Y. Levy, Shai ShalevShwartz		code	-1
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding	Yuval Harel, Ron Meir, Manfred Opper		code	-1
Sum-of-Squares Lower Bounds for Sparse PCA	Tengyu Ma, Avi Wigderson		code	-1
Max-Margin Majority Voting for Learning from Crowds	Tian Tian, Jun Zhu		code	-1
Learning with Incremental Iterative Regularization	Lorenzo Rosasco, Silvia Villa		code	-1
Halting in Random Walk Kernels	Mahito Sugiyama, Karsten M. Borgwardt		code	-1
MCMC for Variationally Sparse Gaussian Processes	James Hensman, Alexander G. de G. Matthews, Maurizio Filippone, Zoubin Ghahramani		code	-1
Less is More: Nyström Computational Regularization	Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco		code	-1
Infinite Factorial Dynamical Model	Isabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando PérezCruz		code	-1
Regularization Path of Cross-Validation Error Lower Bounds	Atsushi Shibagaki, Yoshiki Suzuki, Masayuki Karasuyama, Ichiro Takeuchi		code	-1
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like Environments	Dane S. Corneil, Wulfram Gerstner		code	-1
Teaching Machines to Read and Comprehend	Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom		code	-1
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions	Jonas Mueller, Tommi S. Jaakkola		code	-1
When are Kalman-Filter Restless Bandits Indexable?	Christopher R. Dance, Tomi Silander		code	-1
Segregated Graphs and Marginals of Chain Graph Models	Ilya Shpitser		code	-1
Efficient Non-greedy Optimization of Decision Trees	Mohammad Norouzi, Maxwell D. Collins, Matthew Johnson, David J. Fleet, Pushmeet Kohli		code	-1
Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process	Ye Wang, David B. Dunson		code	-1
Inverse Reinforcement Learning with Locally Consistent Reward Functions	Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet		code	-1
Communication Complexity of Distributed Convex Learning and Optimization	Yossi Arjevani, Ohad Shamir		code	-1
End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture	Jianshu Chen, Ji He, Yelong Shen, Lin Xiao, Xiaodong He, Jianfeng Gao, Xinying Song, Li Deng		code	-1
Subset Selection by Pareto Optimization	Chao Qian, Yang Yu, ZhiHua Zhou		code	-1
On the Accuracy of Self-Normalized Log-Linear Models	Jacob Andreas, Maxim Rabinovich, Michael I. Jordan, Dan Klein		code	-1
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring	Junpei Komiyama, Junya Honda, Hiroshi Nakagawa		code	-1
Is Approval Voting Optimal Given Approval Votes?	Ariel D. Procaccia, Nisarg Shah		code	-1
Regressive Virtual Metric Learning	Michaël Perrot, Amaury Habrard		code	-1
Analysis of Robust PCA via Local Incoherence	Huishuai Zhang, Yi Zhou, Yingbin Liang		code	-1
Learning to Transduce with Unbounded Memory	Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman, Phil Blunsom		code	-1
Max-Margin Deep Generative Models	Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang		code	-1
Spherical Random Features for Polynomial Kernels	Jeffrey Pennington, Felix X. Yu, Sanjiv Kumar		code	-1
Rectified Factor Networks	DjorkArné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter		code	-1
Learning Bayesian Networks with Thousands of Variables	Mauro Scanagatta, Cassio P. de Campos, Giorgio Corani, Marco Zaffalon		code	-1
Matrix Completion Under Monotonic Single Index Models	Ravi Sastry Ganti Mahapatruni, Laura Balzano, Rebecca Willett		code	-1
Visalogy: Answering Visual Analogy Questions	Fereshteh Sadeghi, C. Lawrence Zitnick, Ali Farhadi		code	-1
Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models	Juho Lee, Seungjin Choi		code	-1
Streaming Min-max Hypergraph Partitioning	Dan Alistarh, Jennifer Iglesias, Milan Vojnovic		code	-1
Collaboratively Learning Preferences from Ordinal Data	Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu		code	-1
Biologically Inspired Dynamic Textures for Probing Motion Perception	Jonathan Vacher, Andrew Isaac Meso, Laurent U. Perrinet, Gabriel Peyré		code	-1
Generative Image Modeling Using Spatial LSTMs	Lucas Theis, Matthias Bethge		code	-1
Robust PCA with compressed data	Wooseok Ha, Rina Foygel Barber		code	-1
Sampling from Probabilistic Submodular Models	Alkis Gotovos, S. Hamed Hassani, Andreas Krause		code	-1
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution	Mehrdad Farajtabar, Yichen Wang, Manuel GomezRodriguez, Shuang Li, Hongyuan Zha, Le Song		code	-1
Supervised Learning for Dynamical System Learning	Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon		code	-1
Regret-Based Pruning in Extensive-Form Games	Noam Brown, Tuomas Sandholm		code	-1
Fast Two-Sample Testing with Analytic Representations of Probability Measures	Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic, Arthur Gretton		code	-1
Learning to Segment Object Candidates	Pedro H. O. Pinheiro, Ronan Collobert, Piotr Dollár		code	-1
GP Kernels for Cross-Spectrum Analysis	Kyle R. Ulrich, David E. Carlson, Kafui Dzirasa, Lawrence Carin		code	-1
Secure Multi-party Differential Privacy	Peter Kairouz, Sewoong Oh, Pramod Viswanath		code	-1
Spatial Transformer Networks	Max Jaderberg, Karen Simonyan, Andrew Zisserman, Koray Kavukcuoglu		code	-1
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks	Kevin Scaman, Rémi Lemonnier, Nicolas Vayatis		code	-1
Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms	Yunwen Lei, Ürün Dogan, Alexander Binder, Marius Kloft		code	-1
High-dimensional neural spike train analysis with generalized count linear dynamical systems	Yuanjun Gao, Lars Buesing, Krishna V. Shenoy, John P. Cunningham		code	-1
Learning with a Wasserstein Loss	Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio ArayaPolo, Tomaso A. Poggio		code	-1
b-bit Marginal Regression	Martin Slawski, Ping Li		code	-1
Natural Neural Networks	Guillaume Desjardins, Karen Simonyan, Razvan Pascanu, Koray Kavukcuoglu		code	-1
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference	Edward Meeds, Max Welling		code	-1
Adaptive Primal-Dual Splitting Methods for Statistical Learning and Image Processing	Tom Goldstein, Min Li, Xiaoming Yuan		code	-1
On some provably correct cases of variational inference for topic models	Pranjal Awasthi, Andrej Risteski		code	-1
Collaborative Filtering with Graph Information: Consistency and Scalable Methods	Nikhil Rao, HsiangFu Yu, Pradeep Ravikumar, Inderjit S. Dhillon		code	-1
Combinatorial Bandits Revisited	Richard Combes, Mohammad Sadegh Talebi, Alexandre Proutière, Marc Lelarge		code	-1
Variational Information Maximisation for Intrinsically Motivated Reinforcement Learning	Shakir Mohamed, Danilo Jimenez Rezende		code	-1
A Structural Smoothing Framework For Robust Graph Comparison	Pinar Yanardag, S. V. N. Vishwanathan		code	-1
Competitive Distribution Estimation: Why is Good-Turing Good	Alon Orlitsky, Ananda Theertha Suresh		code	-1
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction	Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama		code	-1
A hybrid sampler for Poisson-Kingman mixture models	Maria Lomeli, Stefano Favaro, Yee Whye Teh		code	-1
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching	Xiao Li, Kannan Ramchandran		code	-1
Local Smoothness in Variance Reduced Optimization	Daniel Vainsencher, Han Liu, Tong Zhang		code	-1
Saliency, Scale and Information: Towards a Unifying Theory	Shafin Rahman, Neil D. B. Bruce		code	-1
Fighting Bandits with a New Kind of Smoothness	Jacob D. Abernethy, Chansoo Lee, Ambuj Tewari		code	-1
Beyond Sub-Gaussian Measurements: High-Dimensional Structured Estimation with Sub-Exponential Designs	Vidyashankar Sivakumar, Arindam Banerjee, Pradeep Ravikumar		code	-1
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction	Rakesh Shivanna, Bibaswan K. Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis R. Bach		code	-1
Convolutional Networks on Graphs for Learning Molecular Fingerprints	David Duvenaud, Dougal Maclaurin, Jorge AguileraIparraguirre, Rafael GómezBombarelli, Timothy Hirzel, Alán AspuruGuzik, Ryan P. Adams		code	-1
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications	Kai Wei, Rishabh K. Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes		code	-1
Tractable Learning for Complex Probability Queries	Jessa Bekker, Jesse Davis, Arthur Choi, Adnan Darwiche, Guy Van den Broeck		code	-1
StopWasting My Gradients: Practical SVRG	Reza Babanezhad, Mohamed Osama Ahmed, Alim Virani, Mark Schmidt, Jakub Konecný, Scott Sallinen		code	-1
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction	Been Kim, Julie A. Shah, Finale DoshiVelez		code	-1
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks	Cengiz Pehlevan, Dmitri B. Chklovskii		code	-1
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators	Changyou Chen, Nan Ding, Lawrence Carin		code	-1
Learning structured densities via infinite dimensional exponential families	Siqi Sun, Mladen Kolar, Jinbo Xu		code	-1
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question	Haoyuan Gao, Junhua Mao, Jie Zhou, Zhiheng Huang, Lei Wang, Wei Xu		code	-1
Variance Reduced Stochastic Gradient Descent with Neighbors	Thomas Hofmann, Aurélien Lucchi, Simon LacosteJulien, Brian McWilliams		code	-1
Sample Efficient Path Integral Control under Uncertainty	Yunpeng Pan, Evangelos A. Theodorou, Michail Kontitsis		code	-1
Stochastic Expectation Propagation	Yingzhen Li, José Miguel HernándezLobato, Richard E. Turner		code	-1
Exactness of Approximate MAP Inference in Continuous MRFs	Nicholas Ruozzi		code	-1
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients	Bo Xie, Yingyu Liang, Le Song		code	-1
Generalization in Adaptive Data Analysis and Holdout Reuse	Cynthia Dwork, Vitaly Feldman, Moritz Hardt, Toniann Pitassi, Omer Reingold, Aaron Roth		code	-1
Market Scoring Rules Act As Opinion Pools For Risk-Averse Agents	Mithun Chakraborty, Sanmay Das		code	-1
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent	Ian EnHsu Yen, Kai Zhong, ChoJui Hsieh, Pradeep Ravikumar, Inderjit S. Dhillon		code	-1
Training Very Deep Networks	Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber		code	-1
Bayesian Active Model Selection with an Application to Automated Audiometry	Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham		code	-1
Particle Gibbs for Infinite Hidden Markov Models	Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani		code	-1
Learning spatiotemporal trajectories from manifold-valued longitudinal data	JeanBaptiste Schiratti, Stéphanie Allassonnière, Olivier Colliot, Stanley Durrleman		code	-1
A Bayesian Framework for Modeling Confidence in Perceptual Decision Making	Koosha Khalvati, Rajesh P. Rao		code	-1
Path-SGD: Path-Normalized Optimization in Deep Neural Networks	Behnam Neyshabur, Ruslan Salakhutdinov, Nathan Srebro		code	-1
On the consistency theory of high dimensional variable screening	Xiangyu Wang, Chenlei Leng, David B. Dunson		code	-1
End-To-End Memory Networks	Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus		code	-1
Spectral Representations for Convolutional Neural Networks	Oren Rippel, Jasper Snoek, Ryan P. Adams		code	-1
Online Gradient Boosting	Alina Beygelzimer, Elad Hazan, Satyen Kale, Haipeng Luo		code	-1
Deep Temporal Sigmoid Belief Networks for Sequence Modeling	Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin		code	-1
Recognizing retinal ganglion cells in the dark	Emile Richard, Georges Goetz, E. J. Chichilnisky		code	-1
A Theory of Decision Making Under Dynamic Context	Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen		code	-1
A Gaussian Process Model of Quasar Spectral Energy Distributions	Andrew C. Miller, Albert Wu, Jeffrey Regier, Jon McAuliffe, Dustin Lang, Prabhat, David Schlegel, Ryan P. Adams		code	-1
Hidden Technical Debt in Machine Learning Systems	D. Sculley, Gary Holt, Daniel Golovin, Eugene Davydov, Todd Phillips, Dietmar Ebner, Vinay Chaudhary, Michael Young, JeanFrançois Crespo, Dan Dennison		code	-1
Local Causal Discovery of Direct Causes and Effects	Tian Gao, Qiang Ji		code	-1
High Dimensional EM Algorithm: Statistical Optimization and Asymptotic Normality	Zhaoran Wang, Quanquan Gu, Yang Ning, Han Liu		code	-1
Revenue Optimization against Strategic Buyers	Mehryar Mohri, Andres Muñoz Medina		code	-1
Deep Convolutional Inverse Graphics Network	Tejas D. Kulkarni, William F. Whitney, Pushmeet Kohli, Joshua B. Tenenbaum		code	-1
Sparse and Low-Rank Tensor Decomposition	Parikshit Shah, Nikhil Rao, Gongguo Tang		code	-1
Minimax Time Series Prediction	Wouter M. Koolen, Alan Malek, Peter L. Bartlett, Yasin AbbasiYadkori		code	-1
Differentially Private Learning of Structured Discrete Distributions	Ilias Diakonikolas, Moritz Hardt, Ludwig Schmidt		code	-1
Variational Dropout and the Local Reparameterization Trick	Diederik P. Kingma, Tim Salimans, Max Welling		code	-1
Sample Complexity of Learning Mahalanobis Distance Metrics	Nakul Verma, Kristin Branson		code	-1
Learning Wake-Sleep Recurrent Attention Models	Jimmy Ba, Ruslan Salakhutdinov, Roger B. Grosse, Brendan J. Frey		code	-1
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso	Eunho Yang, Aurélie C. Lozano		code	-1
Testing Closeness With Unequal Sized Samples	Bhaswar B. Bhattacharya, Gregory Valiant		code	-1
Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach	Wenye Li		code	-1
Neural Adaptive Sequential Monte Carlo	Shixiang Gu, Zoubin Ghahramani, Richard E. Turner		code	-1
Local Expectation Gradients for Black Box Variational Inference	Michalis K. Titsias, Miguel LázaroGredilla		code	-1
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants	Sashank J. Reddi, Ahmed Hefny, Suvrit Sra, Barnabás Póczos, Alexander J. Smola		code	-1
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning	Kevin G. Jamieson, Lalit Jain, Chris Fernandez, Nicholas J. Glattard, Robert D. Nowak		code	-1
Super-Resolution Off the Grid	Qingqing Huang, Sham M. Kakade		code	-1
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms	Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré		code	-1
The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors	Dan Rosenbaum, Yair Weiss		code	-1
Pointer Networks	Oriol Vinyals, Meire Fortunato, Navdeep Jaitly		code	-1
Associative Memory via a Sparse Recovery Model	Arya Mazumdar, Ankit Singh Rawat		code	-1
Robust Spectral Inference for Joint Stochastic Matrix Factorization	Moontae Lee, David Bindel, David M. Mimno		code	-1
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms	Rasmus Kyng, Anup Rao, Sushant Sachdeva		code	-1
Adversarial Prediction Games for Multivariate Losses	Hong Wang, Wei Xing, Kaiser Asif, Brian D. Ziebart		code	-1
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization	Xiangru Lian, Yijun Huang, Yuncheng Li, Ji Liu		code	-1
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images	Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller		code	-1
Efficient and Parsimonious Agnostic Active Learning	TzuKuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire		code	-1
Softstar: Heuristic-Guided Probabilistic Inference	Mathew Monfort, Brenden M. Lake, Brian D. Ziebart, Patrick Lucey, Joshua B. Tenenbaum		code	-1
Grammar as a Foreign Language	Oriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey E. Hinton		code	-1
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices	Martin Slawski, Ping Li, Matthias Hein		code	-1
Winner-Take-All Autoencoders	Alireza Makhzani, Brendan J. Frey		code	-1
Deep Poisson Factor Modeling	Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin		code	-1
Bayesian Optimization with Exponential Convergence	Kenji Kawaguchi, Leslie Pack Kaelbling, Tomás LozanoPérez		code	-1
Sample Complexity of Episodic Fixed-Horizon Reinforcement Learning	Christoph Dann, Emma Brunskill		code	-1
Learning with Relaxed Supervision	Jacob Steinhardt, Percy Liang		code	-1
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's	Vitaly Feldman, Will Perkins, Santosh S. Vempala		code	-1
Accelerated Mirror Descent in Continuous and Discrete Time	Walid Krichene, Alexandre M. Bayen, Peter L. Bartlett		code	-1
The Human Kernel	Andrew Gordon Wilson, Christoph Dann, Christopher G. Lucas, Eric P. Xing		code	-1
Action-Conditional Video Prediction using Deep Networks in Atari Games	Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh		code	-1
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA	James R. Voss, Mikhail Belkin, Luis Rademacher		code	-1
Distributed Submodular Cover: Succinctly Summarizing Massive Data	Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause		code	-1
Community Detection via Measure Space Embedding	Mark Kozdoba, Shie Mannor		code	-1
Basis refinement strategies for linear value function approximation in MDPs	Gheorghe Comanici, Doina Precup, Prakash Panangaden		code	-1
Structured Estimation with Atomic Norms: General Bounds and Applications	Sheng Chen, Arindam Banerjee		code	-1
A Complete Recipe for Stochastic Gradient MCMC	YiAn Ma, Tianqi Chen, Emily B. Fox		code	-1
Bandit Smooth Convex Optimization: Improving the Bias-Variance Tradeoff	Ofer Dekel, Ronen Eldan, Tomer Koren		code	-1
Online Prediction at the Limit of Zero Temperature	Mark Herbster, Stephen Pasteris, Shaona Ghosh		code	-1
Learning Continuous Control Policies by Stochastic Value Gradients	Nicolas Heess, Gregory Wayne, David Silver, Timothy P. Lillicrap, Tom Erez, Yuval Tassa		code	-1
Exploring Models and Data for Image Question Answering	Mengye Ren, Ryan Kiros, Richard S. Zemel		code	-1
Efficient and Robust Automated Machine Learning	Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter		code	-1
Preconditioned Spectral Descent for Deep Learning	David E. Carlson, Edo Collins, YaPing Hsieh, Lawrence Carin, Volkan Cevher		code	-1
A Recurrent Latent Variable Model for Sequential Data	Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C. Courville, Yoshua Bengio		code	-1
Fast Convergence of Regularized Learning in Games	Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire		code	-1
Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation	Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Jürgen Schmidhuber		code	-1
Reflection, Refraction, and Hamiltonian Monte Carlo	Hadi Mohasel Afshar, Justin Domke		code	-1
The Consistency of Common Neighbors for Link Prediction in Stochastic Blockmodels	Purnamrita Sarkar, Deepayan Chakrabarti, Peter J. Bickel		code	-1
Nearly Optimal Private LASSO	Kunal Talwar, Abhradeep Thakurta, Li Zhang		code	-1
Convergence Analysis of Prediction Markets via Randomized Subspace Descent	Rafael M. Frongillo, Mark D. Reid		code	-1
The Poisson Gamma Belief Network	Mingyuan Zhou, Yulai Cong, Bo Chen		code	-1
Convergence rates of sub-sampled Newton methods	Murat A. Erdogdu, Andrea Montanari		code	-1
No-Regret Learning in Bayesian Games	Jason D. Hartline, Vasilis Syrgkanis, Éva Tardos		code	-1
Statistical Topological Data Analysis - A Kernel Perspective	Roland Kwitt, Stefan Huber, Marc Niethammer, Weili Lin, Ulrich Bauer		code	-1
Semi-supervised Sequence Learning	Andrew M. Dai, Quoc V. Le		code	-1
Structured Transforms for Small-Footprint Deep Learning	Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar		code	-1
Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width	Christopher De Sa, Ce Zhang, Kunle Olukotun, Christopher Ré		code	-1
Interpolating Convex and Non-Convex Tensor Decompositions via the Subspace Norm	Qinqing Zheng, Ryota Tomioka		code	-1
Sample Complexity Bounds for Iterative Stochastic Policy Optimization	Marin Kobilarov		code	-1
BinaryConnect: Training Deep Neural Networks with binary weights during propagations	Matthieu Courbariaux, Yoshua Bengio, JeanPierre David		code	-1
Interactive Control of Diverse Complex Characters with Neural Networks	Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, Emanuel Todorov		code	-1
Submodular Hamming Metrics	Jennifer Gillenwater, Rishabh K. Iyer, Bethany Lusch, Rahul Kidambi, Jeff A. Bilmes		code	-1
A Universal Primal-Dual Convex Optimization Framework	Alp Yurtsever, Quoc TranDinh, Volkan Cevher		code	-1
Learning From Small Samples: An Analysis of Simple Decision Heuristics	Özgür Simsek, Marcus Buckmann		code	-1
Explore no more: Improved high-probability regret bounds for non-stochastic bandits	Gergely Neu		code	-1
Fast and Memory Optimal Low-Rank Matrix Approximation	SeYoung Yun, Marc Lelarge, Alexandre Proutière		code	-1
Learnability of Influence in Networks	Harikrishna Narasimhan, David C. Parkes, Yaron Singer		code	-1
Learning Causal Graphs with Small Interventions	Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath		code	-1
Information-theoretic lower bounds for convex optimization with erroneous oracles	Yaron Singer, Jan Vondrák		code	-1
Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial	David I. Inouye, Pradeep Ravikumar, Inderjit S. Dhillon		code	-1
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings	Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin		code	-1
The Self-Normalized Estimator for Counterfactual Learning	Adith Swaminathan, Thorsten Joachims		code	-1
Fast Lifted MAP Inference via Partitioning	Somdeb Sarkhel, Parag Singla, Vibhav Gogate		code	-1
Data Generation as Sequential Decision Making	Philip Bachman, Doina Precup		code	-1
On Elicitation Complexity	Rafael M. Frongillo, Ian A. Kash		code	-1
Decomposition Bounds for Marginal MAP	Wei Ping, Qiang Liu, Alexander Ihler		code	-1
Discrete Rényi Classifiers	Meisam Razaviyayn, Farzan Farnia, David Tse		code	-1
A class of network models recoverable by spectral clustering	Yali Wan, Marina Meila		code	-1
Skip-Thought Vectors	Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Raquel Urtasun, Antonio Torralba, Sanja Fidler		code	-1
Rate-Agnostic (Causal) Structure Learning	Sergey M. Plis, David Danks, Cynthia Freeman, Vince D. Calhoun		code	-1
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric	Vivien Seguy, Marco Cuturi		code	-1
Consistent Multilabel Classification	Oluwasanmi Koyejo, Nagarajan Natarajan, Pradeep Ravikumar, Inderjit S. Dhillon		code	-1
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions	Amar Shah, Zoubin Ghahramani		code	-1
Cornering Stationary and Restless Mixing Bandits with Remix-UCB	Julien Audiffren, Liva Ralaivola		code	-1
Semi-Supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data	Danilo Bzdok, Michael Eickenberg, Olivier Grisel, Bertrand Thirion, Gaël Varoquaux		code	-1
Gaussian Process Random Fields	David A. Moore, Stuart J. Russell		code	-1
M-Statistic for Kernel Change-Point Detection	Shuang Li, Yao Xie, Hanjun Dai, Le Song		code	-1
Adaptive Online Learning	Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan		code	-1
A Universal Catalyst for First-Order Optimization	Hongzhou Lin, Julien Mairal, Zaïd Harchaoui		code	-1
Inference for determinantal point processes without spectral knowledge	Rémi Bardenet, Michalis K. Titsias		code	-1
Kullback-Leibler Proximal Variational Inference	Mohammad E. Khan, Pierre Baqué, François Fleuret, Pascal Fua		code	-1
Semi-Proximal Mirror-Prox for Nonsmooth Composite Minimization	Niao He, Zaïd Harchaoui		code	-1
LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements	Christos Thrampoulidis, Ehsan Abbasi, Babak Hassibi		code	-1
From random walks to distances on unweighted graphs	Tatsunori B. Hashimoto, Yi Sun, Tommi S. Jaakkola		code	-1
Bayesian dark knowledge	Anoop Korattikara Balan, Vivek Rathod, Kevin P. Murphy, Max Welling		code	-1
Matrix Completion with Noisy Side Information	KaiYang Chiang, ChoJui Hsieh, Inderjit S. Dhillon		code	-1
Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation	Scott W. Linderman, Matthew J. Johnson, Ryan P. Adams		code	-1
On-the-Job Learning with Bayesian Decision Theory	Keenon Werling, Arun Tejasvi Chaganty, Percy Liang, Christopher D. Manning		code	-1
Calibrated Structured Prediction	Volodymyr Kuleshov, Percy Liang		code	-1
Learning Structured Output Representation using Deep Conditional Generative Models	Kihyuk Sohn, Honglak Lee, Xinchen Yan		code	-1
Time-Sensitive Recommendation From Recurrent User Activities	Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song		code	-1
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels	Felipe A. Tobar, Thang D. Bui, Richard E. Turner		code	-1
A Market Framework for Eliciting Private Data	Bo Waggoner, Rafael M. Frongillo, Jacob D. Abernethy		code	-1
Lifted Inference Rules With Constraints	Happy Mittal, Anuj Mahajan, Vibhav Gogate, Parag Singla		code	-1
Gradient Estimation Using Stochastic Computation Graphs	John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel		code	-1
Model-Based Relative Entropy Stochastic Search	Abbas Abdolmaleki, Rudolf Lioutikov, Jan Peters, Nuno Lau, Luís Paulo Reis, Gerhard Neumann		code	-1
Semi-supervised Learning with Ladder Networks	Antti Rasmus, Mathias Berglund, Mikko Honkala, Harri Valpola, Tapani Raiko		code	-1
Embedding Inference for Structured Multilabel Prediction	Farzaneh Mirzazadeh, Siamak Ravanbakhsh, Nan Ding, Dale Schuurmans		code	-1
Copula variational inference	Dustin Tran, David M. Blei, Edoardo M. Airoldi		code	-1
Recursive Training of 2D-3D Convolutional Networks for Neuronal Boundary Prediction	Kisuk Lee, Aleksandar Zlateski, Ashwin Vishwanathan, H. Sebastian Seung		code	-1
A Dual Augmented Block Minimization Framework for Learning with Limited Memory	Ian EnHsu Yen, ShanWei Lin, ShouDe Lin		code	-1
Optimal Testing for Properties of Distributions	Jayadev Acharya, Constantinos Daskalakis, Gautam Kamath		code	-1
Efficient Learning of Continuous-Time Hidden Markov Models for Disease Progression	YuYing Liu, Shuang Li, Fuxin Li, Le Song, James M. Rehg		code	-1
Expectation Particle Belief Propagation	Thibaut Liénart, Yee Whye Teh, Arnaud Doucet		code	-1
Latent Bayesian melding for integrating individual and population models	Mingjun Zhong, Nigel H. Goddard, Charles Sutton		code	-1