Table of Contents

• Only H is left: Near-tight Episodic PAC RL [doi]
• Learning to Poke by Poking: Experiential Learning of Intuitive Physics [doi]
• Cyclades: Conflict-free Asynchronous Machine Learning [doi]
• Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How MuchBryan D. He, Christopher De Sa, Ioannis Mitliagkas, Christopher Ré. 1-9 [doi]
• Deep ADMM-Net for Compressive Sensing MRIYan Yang, Jian Sun 0001, Huibin Li, ZongBen Xu. 10-18 [doi]
• A scaled Bregman theorem with applicationsRichard Nock, Aditya Krishna Menon, Cheng Soon Ong. 19-27 [doi]
• Swapout: Learning an ensemble of deep architecturesSaurabh Singh, Derek Hoiem, David A. Forsyth. 28-36 [doi]
• On Regularizing Rademacher Observation LossesRichard Nock. 37-45 [doi]
• Without-Replacement Sampling for Stochastic Gradient MethodsOhad Shamir. 46-54 [doi]
• Fast and Provably Good Seedings for k-MeansOlivier Bachem, Mario Lucic, Seyed Hamed Hassani, Andreas Krause 0001. 55-63 [doi]
• Unsupervised Learning for Physical Interaction through Video PredictionChelsea Finn, Ian J. Goodfellow, Sergey Levine. 64-72 [doi]
• High-Rank Matrix Completion and Clustering under Self-Expressive ModelsEhsan Elhamifar. 73-81 [doi]
• Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingJiajun Wu 0001, Chengkai Zhang, Tianfan Xue, Bill Freeman, Josh Tenenbaum. 82-90 [doi]
• Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional NetworksTianfan Xue, Jiajun Wu 0001, Katherine L. Bouman, Bill Freeman. 91-99 [doi]
• Human Decision-Making under Limited TimePedro A. Ortega, Alan A. Stocker. 100-108 [doi]
• Incremental Boosting Convolutional Neural Network for Facial Action Unit RecognitionShizhong Han, Zibo Meng, Ahmed-Shehab Khan, Yan Tong. 109-117 [doi]
• Natural-Parameter Networks: A Class of Probabilistic Neural NetworksHao Wang 0014, Xingjian Shi, Dit-Yan Yeung. 118-126 [doi]
• Tree-Structured Reinforcement Learning for Sequential Object LocalizationZequn Jie, Xiaodan Liang, Jiashi Feng, Xiaojie Jin, Wen Lu, Shuicheng Yan. 127-135 [doi]
• Unsupervised Domain Adaptation with Residual Transfer NetworksMingsheng Long, Han Zhu, Jianmin Wang 0001, Michael I. Jordan. 136-144 [doi]
• Verification Based Solution for Structured MAB ProblemsZohar S. Karnin. 145-153 [doi]
• Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum GamesMaximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre M. Bayen. 154-162 [doi]
• Linear dynamical neural population models through nonlinear embeddingsYuanjun Gao, Evan W. Archer, Liam Paninski, John P. Cunningham. 163-171 [doi]
• SURGE: Surface Regularized Geometry Estimation from a Single ImagePeng Wang 0001, Xiaohui Shen, Bryan Russell, Scott Cohen, Brian L. Price, Alan L. Yuille. 172-180 [doi]
• Interpretable Distribution Features with Maximum Testing PowerWittawat Jitkrittum, Zoltán Szabó 0001, Kacper P. Chwialkowski, Arthur Gretton. 181-189 [doi]
• Sorting out typicality with the inverse moment matrix SOS polynomialEdouard Pauwels, Jean B. Lasserre. 190-198 [doi]
• Multi-armed Bandits: Competing with Optimal SequencesZohar S. Karnin, Oren Anava. 199-207 [doi]
• Multivariate tests of association based on univariate testsRuth Heller, Yair Heller. 208-216 [doi]
• Learning What and Where to DrawScott E. Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee. 217-225 [doi]
• The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALMDamek Davis, Brent Edmunds, Madeleine Udell. 226-234 [doi]
• Integrated perception with recurrent multi-task neural networksHakan Bilen, Andrea Vedaldi. 235-243 [doi]
• Combining Low-Density Separators with CNNsYu-Xiong Wang, Martial Hebert. 244-252 [doi]
• CNNpack: Packing Convolutional Neural Networks in the Frequency DomainYunhe Wang, Chang Xu, Shan You, Dacheng Tao, Chao Xu 0006. 253-261 [doi]
• Cooperative Graphical ModelsJosip Djolonga, Stefanie Jegelka, Sebastian Tschiatschek, Andreas Krause 0001. 262-270 [doi]
• f-GAN: Training Generative Neural Samplers using Variational Divergence MinimizationSebastian Nowozin, Botond Cseke, Ryota Tomioka. 271-279 [doi]
• Bayesian Optimization for Probabilistic ProgramsTom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank Wood. 280-288 [doi]
• Hierarchical Question-Image Co-Attention for Visual Question AnsweringJiasen Lu, Jianwei Yang, Dhruv Batra, Devi Parikh. 289-297 [doi]
• Optimal Sparse Linear Encoders and Sparse PCAMalik Magdon-Ismail, Christos Boutsidis. 298-306 [doi]
• FPNN: Field Probing Neural Networks for 3D DataYangyan Li, Sören Pirk, Hao Su, Charles Ruizhongtai Qi, Leonidas J. Guibas. 307-315 [doi]
• CRF-CNN: Modeling Structured Information in Human Pose EstimationXiao Chu, Wanli Ouyang, Hongsheng Li, Xiaogang Wang. 316-324 [doi]
• Fairness in Learning: Classic and Contextual BanditsMatthew Joseph, Michael Kearns, Jamie H. Morgenstern, Aaron Roth. 325-333 [doi]
• Joint M-Best-Diverse Labelings as a Parametric Submodular MinimizationAlexander Kirillov, Alexander Shekhovtsov, Carsten Rother, Bogdan Savchynskyy. 334-342 [doi]
• Domain Separation NetworksKonstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan. 343-351 [doi]
• DISCO Nets : DISsimilarity COefficients NetworksDiane Bouchacourt, Pawan Kumar Mudigonda, Sebastian Nowozin. 352-360 [doi]
• Multimodal Residual Learning for Visual QAJin-Hwa Kim, Sang-Woo Lee, Dong-Hyun Kwak, Min-Oh Heo, Jeonghee Kim, Jungwoo Ha, Byoung-Tak Zhang. 361-369 [doi]
• CMA-ES with Optimal Covariance Update and Storage ComplexityOswin Krause, Dídac Rodríguez Arbonès, Christian Igel. 370-378 [doi]
• R-FCN: Object Detection via Region-based Fully Convolutional NetworksJifeng Dai, Yi Li, Kaiming He, Jian Sun. 379-387 [doi]
• GAP Safe Screening Rules for Sparse-Group LassoEugène Ndiaye, Olivier Fercoq, Alexandre Gramfort, Joseph Salmon. 388-396 [doi]
• Learning and Forecasting Opinion Dynamics in Social NetworksAbir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez-Rodriguez. 397-405 [doi]
• Gradient-based Sampling: An Adaptive Importance Sampling for Least-squaresRong Zhu. 406-414 [doi]
• Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the BlanksHao Wang 0014, Xingjian Shi, Dit-Yan Yeung. 415-423 [doi]
• Mutual information for symmetric rank-one matrix estimation: A proof of the replica formulaJean Barbier, Mohamad Dia, Nicolas Macris, Florent Krzakala, Thibault Lesieur, Lenka Zdeborová. 424-432 [doi]
• A Unified Approach for Learning the Parameters of Sum-Product NetworksHan Zhao, Pascal Poupart, Geoffrey J. Gordon. 433-441 [doi]
• Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated ImagesJunhua Mao, Jiajing Xu, Kevin Jing, Alan L. Yuille. 442-450 [doi]
• Stochastic Online AUC MaximizationYiming Ying, Longyin Wen, Siwei Lyu. 451-459 [doi]
• The Generalized Reparameterization GradientFrancisco J. R. Ruiz, Michalis K. Titsias, David M. Blei. 460-468 [doi]
• Coupled Generative Adversarial NetworksMing-Yu Liu 0001, Oncel Tuzel. 469-477 [doi]
• Exponential Family EmbeddingsMaja R. Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei. 478-486 [doi]
• Variational Information Maximization for Feature SelectionShuyang Gao, Greg Ver Steeg, Aram Galstyan. 487-495 [doi]
• Operator Variational InferenceRajesh Ranganath, Dustin Tran, Jaan Altosaar, David M. Blei. 496-504 [doi]
• Fast learning rates with heavy-tailed lossesVu C. Dinh, Lam S. Ho, Binh T. Nguyen, Duy Nguyen. 505-513 [doi]
• Budgeted stream-based active learning via adaptive submodular maximizationKaito Fujii, Hisashi Kashima. 514-522 [doi]
• Learning feed-forward one-shot learnersLuca Bertinetto, João F. Henriques, Jack Valmadre, Philip H. S. Torr, Andrea Vedaldi. 523-531 [doi]
• Learning User Perceived Clusters with Feature-Level SupervisionTing-Yu Cheng, Guiguan Lin, Xinyang Gong, Kang-Jun Liu, Shan-Hung Wu. 532-540 [doi]
• Robust Spectral Detection of Global Structures in the Data by Learning a RegularizationPan Zhang. 541-549 [doi]
• Residual Networks Behave Like Ensembles of Relatively Shallow NetworksAndreas Veit, Michael J. Wilber, Serge J. Belongie. 550-558 [doi]
• Adversarial Multiclass Classification: A Risk Minimization PerspectiveRizal Fathony, Anqi Liu, Kaiser Asif, Brian D. Ziebart. 559-567 [doi]
• Solving Random Systems of Quadratic Equations via Truncated Generalized Gradient FlowGang Wang, Georgios B. Giannakis. 568-576 [doi]
• Coin Betting and Parameter-Free Online LearningFrancesco Orabona, Dávid Pál. 577-585 [doi]
• Deep Learning without Poor Local MinimaKenji Kawaguchi. 586-594 [doi]
• Testing for Differences in Gaussian Graphical Models: Applications to Brain ConnectivityEugene Belilovsky, Gaël Varoquaux, Matthew B. Blaschko. 595-603 [doi]
• A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++Dennis Wei. 604-612 [doi]
• Generating Videos with Scene DynamicsCarl Vondrick, Hamed Pirsiavash, Antonio Torralba. 613-621 [doi]
• Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural NetworksDaniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman. 622-630 [doi]
• A Powerful Generative Model Using Random Weights for the Deep Image RepresentationKun He, Yan Wang, John E. Hopcroft. 631-639 [doi]
• Optimizing affinity-based binary hashing using auxiliary coordinatesRamin Raziperchikolaei, Miguel Á. Carreira-Perpiñán. 640-648 [doi]
• Double Thompson Sampling for Dueling BanditsHuasen Wu, Xin Liu. 649-657 [doi]
• Generating Images with Perceptual Similarity Metrics based on Deep NetworksAlexey Dosovitskiy, Thomas Brox. 658-666 [doi]
• Dynamic Filter NetworksXu Jia, Bert De Brabandere, Tinne Tuytelaars, Luc Van Gool. 667-675 [doi]
• A Simple Practical Accelerated Method for Finite SumsAaron Defazio. 676-684 [doi]
• Barzilai-Borwein Step Size for Stochastic Gradient DescentConghui Tan, Shiqian Ma, Yu-Hong Dai, Yuqiu Qian. 685-693 [doi]
• On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and ScalabilityGuillaume Papa, Aurélien Bellet, Stéphan Clémençon. 694-702 [doi]
• Optimal spectral transportation with application to music transcriptionRémi Flamary, Cédric Févotte, Nicolas Courty, Valentin Emiya. 703-711 [doi]
• Regularized Nonlinear AccelerationDamien Scieur, Alexandre d'Aspremont, Francis R. Bach. 712-720 [doi]
• SPALS: Fast Alternating Least Squares via Implicit Leverage Scores SamplingDehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros. 721-729 [doi]
• Single-Image Depth Perception in the WildWeifeng Chen, Zhao Fu, Dawei Yang, Jia Deng. 730-738 [doi]
• Computational and Statistical Tradeoffs in Learning to RankAshish Khetan, Sewoong Oh. 739-747 [doi]
• Online Convex Optimization with Unconstrained Domains and LossesAshok Cutkosky, Kwabena A. Boahen. 748-756 [doi]
• An ensemble diversity approach to supervised binary hashingMiguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei. 757-765 [doi]
• Efficient Globally Convergent Stochastic Optimization for Canonical Correlation AnalysisWeiran Wang, Jialei Wang, Dan Garber, Dan Garber, Nati Srebro. 766-774 [doi]
• The Power of Adaptivity in Identifying Statistical AlternativesKevin G. Jamieson, Daniel Haas, Benjamin Recht. 775-783 [doi]
• On Explore-Then-Commit strategiesAurélien Garivier, Tor Lattimore, Emilie Kaufmann. 784-792 [doi]
• Sublinear Time Orthogonal Tensor DecompositionZhao Song, David P. Woodruff, Huan Zhang. 793-801 [doi]
• DECOrrelated feature space partitioning for distributed sparse regressionXiangyu Wang, David B. Dunson, Chenlei Leng. 802-810 [doi]
• Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action RecognitionJinzhuo Wang, Wenmin Wang, Xiongtao Chen, Ronggang Wang, Wen Gao 0001. 811-819 [doi]
• Dual Learning for Machine TranslationDi He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma. 820-828 [doi]
• Dialog-based Language LearningJason Weston. 829-837 [doi]
• Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph RecognitionThéodore Bluche. 838-846 [doi]
• Temporal Regularized Matrix Factorization for High-dimensional Time Series PredictionHsiang-Fu Yu, Nikhil Rao, Inderjit S. Dhillon. 847-855 [doi]
• Active Nearest-Neighbor Learning in Metric SpacesAryeh Kontorovich, Sivan Sabato, Ruth Urner. 856-864 [doi]
• Proximal Deep Structured ModelsShenlong Wang, Sanja Fidler, Raquel Urtasun. 865-873 [doi]
• Faster Projection-free Convex Optimization over the SpectrahedronDan Garber, Dan Garber. 874-882 [doi]
• Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming ApproachRémi Lam, Karen Willcox, David H. Wolpert. 883-891 [doi]
• SoundNet: Learning Sound Representations from Unlabeled VideoYusuf Aytar, Carl Vondrick, Antonio Torralba. 892-900 [doi]
• Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural NetworksTim Salimans, Diederik P. Kingma. 901 [doi]
• Efficient Second Order Online Learning by SketchingHaipeng Luo, Alekh Agarwal, Nicolò Cesa-Bianchi, John Langford. 902-910 [doi]
• Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral AnalysisYoshinobu Kawahara. 911-919 [doi]
• Distributed Flexible Nonlinear Tensor FactorizationShandian Zhe, Kai Zhang, Pengyuan Wang, Kuang-Chih Lee, Zenglin Xu, Yuan Qi, Zoubin Ghahramani. 920-928 [doi]
• The Robustness of Estimator CompositionPingfan Tang, Jeff M. Phillips. 929-937 [doi]
• Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating BatsBipin Rajendran, Pulkit Tandon, Yash H. Malviya. 938-946 [doi]
• PerforatedCNNs: Acceleration through Elimination of Redundant ConvolutionsMikhail Figurnov, Aizhan Ibraimova, Dmitry P. Vetrov, Pushmeet Kohli. 947-955 [doi]
• Differential Privacy without SensitivityKentaro Minami, Hitomi Arai, Issei Sato, Hiroshi Nakagawa. 956-964 [doi]
• Optimal Cluster Recovery in the Labeled Stochastic Block ModelSe-Young Yun, Alexandre Proutière. 965-973 [doi]
• Even Faster SVD Decomposition Yet Without Agonizing PainZeyuan Allen Zhu, Yuanzhi Li. 974-982 [doi]
• An algorithm for L1 nearest neighbor search via monotonic embeddingXinan Wang, Sanjoy Dasgupta. 983-991 [doi]
• Gaussian Process Bandit Optimisation with Multi-fidelity EvaluationsKirthevasan Kandasamy, Gautam Dasarathy, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos. 992-1000 [doi]
• Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured PolytopesDan Garber, Ofer Meshi. 1001-1009 [doi]
• Efficient Nonparametric Smoothness EstimationShashank Singh, Simon S. Du, Barnabás Póczos. 1010-1018 [doi]
• A Theoretically Grounded Application of Dropout in Recurrent Neural NetworksYarin Gal, Zoubin Ghahramani. 1019-1027 [doi]
• Fast ε-free Inference of Simulation Models with Bayesian Conditional Density EstimationGeorge Papamakarios, Iain Murray. 1028-1036 [doi]
• Direct Feedback Alignment Provides Learning in Deep Neural NetworksArild Nøkland. 1037-1045 [doi]
• Safe and Efficient Off-Policy Reinforcement LearningRémi Munos, Tom Stepleton, Anna Harutyunyan, Marc G. Bellemare. 1046-1054 [doi]
• A Multi-Batch L-BFGS Method for Machine LearningAlbert S. Berahas, Jorge Nocedal, Martin Takác. 1055-1063 [doi]
• Semiparametric Differential Graph ModelsPan Xu, Quanquan Gu. 1064-1072 [doi]
• Rényi Divergence Variational InferenceYingzhen Li, Richard E. Turner. 1073-1081 [doi]
• Doubly Convolutional Neural NetworksShuangfei Zhai, Yu Cheng, Zhongfei (Mark) Zhang, Weining Lu. 1082-1090 [doi]
• Density Estimation via Discrepancy Based Adaptive Sequential PartitionDangna Li, Kun Yang, Wing Hung Wong. 1091-1099 [doi]
• How Deep is the Feature Analysis underlying Rapid Visual Categorization?Sven Eberhardt, Jonah G. Cader, Thomas Serre. 1100-1108 [doi]
• VIME: Variational Information Maximizing ExplorationRein Houthooft, Xi Chen, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel. 1109-1117 [doi]
• Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the BrainTimothy N. Rubin, Oluwasanmi Koyejo, Michael N. Jones, Tal Yarkoni. 1118-1126 [doi]
• Solving Marginal MAP Problems with NP Oracles and Parity ConstraintsYexiang Xue, Zhiyuan Li, Stefano Ermon, Carla P. Gomes, Bart Selman. 1127-1135 [doi]
• Multi-view Anomaly Detection via Robust Probabilistic Latent Variable ModelsTomoharu Iwata, Makoto Yamada. 1136-1144 [doi]
• Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum OptimizationSashank J. Reddi, Suvrit Sra, Barnabás Póczos, Alexander J. Smola. 1145-1153 [doi]
• Variance Reduction in Stochastic Gradient Langevin DynamicsKumar Avinava Dubey, Sashank J. Reddi, Sinead A. Williamson, Barnabás Póczos, Alexander J. Smola, Eric P. Xing. 1154-1162 [doi]
• Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised LearningMehdi Sajjadi, Mehran Javanmardi, Tolga Tasdizen. 1163-1171 [doi]
• Dense Associative Memory for Pattern RecognitionDmitry Krotov, John J. Hopfield. 1172-1180 [doi]
• Causal Bandits: Learning Good Interventions via Causal InferenceFinnian Lattimore, Tor Lattimore, Mark D. Reid. 1181-1189 [doi]
• Refined Lower Bounds for Adversarial BanditsSébastien Gerchinovitz, Tor Lattimore. 1190-1198 [doi]
• Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative LearningGang Niu, Marthinus Christoffel du Plessis, Tomoya Sakai, Yao Ma, Masashi Sugiyama. 1199-1207 [doi]
• Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/\epsilon)Yi Xu, Yan Yan, Qihang Lin, Tianbao Yang. 1208-1216 [doi]
• Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional EstimatorsShashank Singh, Barnabás Póczos. 1217-1225 [doi]
• A state-space model of cross-region dynamic connectivity in MEG/EEGYing Yang, Elissa Aminoff, Michael J. Tarr, Robert E. Kass. 1226-1234 [doi]
• What Makes Objects Similar: A Unified Multi-Metric Learning ApproachHan-Jia Ye, De-Chuan Zhan, Xue-Min Si, Yuan Jiang, Zhi-Hua Zhou. 1235-1243 [doi]
• Adaptive Maximization of Pointwise Submodular Functions With Budget ConstraintNguyen Cuong, Huan Xu. 1244-1252 [doi]
• Dueling Bandits: Beyond Condorcet Winners to General Tournament SolutionsSiddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal 0001. 1253-1261 [doi]
• Local Similarity-Aware Deep Feature EmbeddingChen Huang, Chen Change Loy, Xiaoou Tang. 1262-1270 [doi]
• A Communication-Efficient Parallel Algorithm for Decision TreeQi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu. 1271-1279 [doi]
• Convex Two-Layer Modeling with Latent StructureVignesh Ganapathiraman, Xinhua Zhang, Yaoliang Yu, Junfeng Wen. 1280-1288 [doi]
• Sampling for Bayesian Program LearningKevin Ellis, Armando Solar-Lezama, Josh Tenenbaum. 1289-1297 [doi]
• Learning Kernels with Random FeaturesAman Sinha, John C. Duchi. 1298-1306 [doi]
• Optimal Tagging with Markov Chain OptimizationNir Rosenfeld, Amir Globerson. 1307-1315 [doi]
• Crowdsourced Clustering: Querying Edges vs TrianglesRamya Korlakai Vinayak, Babak Hassibi. 1316-1324 [doi]
• Mixed vine copulas as joint models of spike counts and local field potentialsArno Onken, Stefano Panzeri. 1325-1333 [doi]
• Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagationEmmanuel Abbe, Colin Sandon. 1334-1342 [doi]
• Adaptive Concentration Inequalities for Sequential Decision ProblemsShengjia Zhao, Enze Zhou, Ashish Sabharwal, Stefano Ermon. 1343-1351 [doi]
• Nested Mini-Batch K-MeansJames Newling, François Fleuret. 1352-1360 [doi]
• Deep Learning Models of the Retinal Response to Natural ScenesLane McIntosh, Niru Maheswaranathan, Aran Nayebi, Surya Ganguli, Stephen Baccus. 1361-1369 [doi]
• Preference Completion from Partial RankingsSuriya Gunasekar, Oluwasanmi Koyejo, Joydeep Ghosh. 1370-1378 [doi]
• Dynamic Network Surgery for Efficient DNNsYiwen Guo, Anbang Yao, Yurong Chen. 1379-1387 [doi]
• Learning a Metric Embedding for Face Recognition using the Multibatch MethodOren Tadmor, Tal Rosenwein, Shai Shalev-Shwartz, Yonatan Wexler, Amnon Shashua. 1388-1389 [doi]
• A Pseudo-Bayesian Algorithm for Robust PCATae Hyun Oh, Yasuyuki Matsushita, In-So Kweon, David P. Wipf. 1390-1398 [doi]
• End-to-End Kernel Learning with Supervised Convolutional Kernel NetworksJulien Mairal. 1399-1407 [doi]
• Stochastic Variance Reduction Methods for Saddle-Point ProblemsBalamurugan Palaniappan, Francis R. Bach. 1408-1416 [doi]
• Flexible Models for Microclustering with Application to Entity ResolutionBrenda Betancourt, Giacomo Zanella, Jeffrey W. Miller, Hanna M. Wallach, Abbas Zaidi, Beka Steorts. 1417-1425 [doi]
• Catching heuristics are optimal control policiesBoris Belousov, Gerhard Neumann, Constantin A. Rothkopf, Jan R. Peters. 1426-1434 [doi]
• Bayesian optimization under mixed constraints with a slack-variable augmented LagrangianVictor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel. 1435-1443 [doi]
• Adaptive Neural CompilationRudy R. Bunel, Alban Desmaison, Pawan Kumar Mudigonda, Pushmeet Kohli, Philip H. S. Torr. 1444-1452 [doi]
• Synthesis of MCMC and Belief PropagationSungsoo Ahn, Michael Chertkov, Jinwoo Shin. 1453-1461 [doi]
• Learning Treewidth-Bounded Bayesian Networks with Thousands of VariablesMauro Scanagatta, Giorgio Corani, Cassio Polpo de Campos, Marco Zaffalon. 1462-1470 [doi]
• Unifying Count-Based Exploration and Intrinsic MotivationMarc G. Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, Rémi Munos. 1471-1479 [doi]
• Large Margin Discriminant Dimensionality Reduction in Prediction SpaceMohammad J. Saberian, Jose Costa Pereira, Nuno Vasconcelos, Can Xu. 1480-1488 [doi]
• Stochastic Structured Prediction under Bandit FeedbackArtem Sokolov, Julia Kreutzer, Stefan Riezler, Christopher Lo. 1489-1497 [doi]
• Simple and Efficient Weighted Minwise HashingAnshumali Shrivastava. 1498-1506 [doi]
• Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set EstimationIlija Bogunovic, Jonathan Scarlett, Andreas Krause 0001, Volkan Cevher. 1507-1515 [doi]
• Structured Sparse Regression via Greedy Hard ThresholdingPrateek Jain 0002, Nikhil Rao, Inderjit S. Dhillon. 1516-1524 [doi]
• Understanding Probabilistic Sparse Gaussian Process ApproximationsMatthias Bauer, Mark van der Wilk, Carl Edward Rasmussen. 1525-1533 [doi]
• SEBOOST - Boosting Stochastic Learning Using Subspace Optimization TechniquesElad Richardson, Rom Herskovitz, Boris Ginsburg, Michael Zibulevsky. 1534-1542 [doi]
• Generating Long-term Trajectories Using Deep Hierarchical NetworksStephan Zheng, Yisong Yue, Jennifer Hobbs. 1543-1551 [doi]
• Learning Tree Structured Potential GamesVikas K. Garg, Tommi S. Jaakkola. 1552-1560 [doi]
• Observational-Interventional Priors for Dose-Response LearningRicardo Silva. 1561-1569 [doi]
• Learning from Rational Behavior: Predicting Solutions to Unknown Linear ProgramsShahin Jabbari, Ryan M. Rogers, Aaron Roth, Steven Z. Wu. 1570-1578 [doi]
• Identification and Overidentification of Linear Structural Equation ModelsBryant Chen. 1579-1587 [doi]
• Adaptive Skills Adaptive Partitions (ASAP)Daniel J. Mankowitz, Timothy Arthur Mann, Shie Mannor. 1588-1596 [doi]
• Multiple-Play Bandits in the Position-Based ModelPaul Lagrée, Claire Vernade, Olivier Cappé. 1597-1605 [doi]
• Optimal Black-Box Reductions Between Optimization ObjectivesZeyuan Allen Zhu, Elad Hazan. 1606-1614 [doi]
• On Valid Optimal Assignment Kernels and Applications to Graph ClassificationNils M. Kriege, Pierre-Louis Giscard, Richard C. Wilson. 1615-1623 [doi]
• Robustness of classifiers: from adversarial to random noiseAlhussein Fawzi, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard. 1624-1632 [doi]
• A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix SensingMing Lin, Jieping Ye. 1633-1641 [doi]
• Exploiting the Structure: Stochastic Gradient Methods Using Raw ClustersZeyuan Allen Zhu, Yang Yuan, Karthik Sridharan. 1642-1650 [doi]
• Combinatorial Multi-Armed Bandit with General Reward FunctionsWei Chen, Wei Hu, Fu Li, Jian Li, Yu Liu, Pinyan Lu. 1651-1659 [doi]
• Boosting with AbstentionCorinna Cortes, Giulia DeSalvo, Mehryar Mohri. 1660-1668 [doi]
• Regret of Queueing BanditsSubhashini Krishnasamy, Rajat Sen, Ramesh Johari, Sanjay Shakkottai. 1669-1677 [doi]
• Deep Learning GamesDale Schuurmans, Martin A. Zinkevich. 1678-1686 [doi]
• Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral MethodsAntoine Gautier, Quynh N. Nguyen, Matthias Hein 0001. 1687-1695 [doi]
• Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D SupervisionXinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, Honglak Lee. 1696-1704 [doi]
• A Credit Assignment Compiler for Joint PredictionKai-Wei Chang, He He, Stéphane Ross, Hal Daumé III, John Langford. 1705-1713 [doi]
• Accelerating Stochastic Composition OptimizationMengdi Wang, Ji Liu, Ethan Fang. 1714-1722 [doi]
• Reward Augmented Maximum Likelihood for Neural Structured PredictionMohammad Norouzi, Samy Bengio, Zhifeng Chen, Navdeep Jaitly, Mike Schuster, Yonghui Wu, Dale Schuurmans. 1723-1731 [doi]
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• Variational Inference in Mixed Probabilistic Submodular ModelsJosip Djolonga, Sebastian Tschiatschek, Andreas Krause 0001. 1759-1767 [doi]
• Correlated-PCA: Principal Components' Analysis when Data and Noise are CorrelatedNamrata Vaswani, Han Guo. 1768-1776 [doi]
• The Multi-fidelity Multi-armed BanditKirthevasan Kandasamy, Gautam Dasarathy, Barnabás Póczos, Jeff G. Schneider. 1777-1785 [doi]
• Anchor-Free Correlated Topic Modeling: Identifiability and AlgorithmKejun Huang, Xiao Fu, Nikos D. Sidiropoulos. 1786-1794 [doi]
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• Learned Region Sparsity and Diversity Also Predicts Visual AttentionZijun Wei, Hossein Adeli, Minh Hoai, Gregory J. Zelinsky, Dimitris Samaras. 1894-1902 [doi]
• End-to-End Goal-Driven Web NavigationRodrigo Nogueira, KyungHyun Cho. 1903-1911 [doi]
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• Privacy Odometers and Filters: Pay-as-you-Go CompositionRyan M. Rogers, Salil P. Vadhan, Aaron Roth, Jonathan Ullman. 1921-1929 [doi]
• Minimax Estimation of Maximum Mean Discrepancy with Radial KernelsIlya O. Tolstikhin, Bharath K. Sriperumbudur, Bernhard Schölkopf. 1930-1938 [doi]
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• Hierarchical Object Representation for Open-Ended Object Category Learning and RecognitionSeyed Hamidreza Kasaei, Ana Maria Tomé, Luís Seabra Lopes. 1948-1956 [doi]
• Relevant sparse codes with variational information bottleneckMatthew Chalk, Olivier Marre, Gasper Tkacik. 1957-1965 [doi]
• Combinatorial Energy Learning for Image SegmentationJeremy B. Maitin-Shepard, Viren Jain, Michal Januszewski, Peter Li, Pieter Abbeel. 1966-1974 [doi]
• Orthogonal Random FeaturesFelix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel Holtmann-Rice, Sanjiv Kumar. 1975-1983 [doi]
• Fast Active Set Methods for Online Spike Inference from Calcium ImagingJohannes Friedrich, Liam Paninski. 1984-1992 [doi]
• Diffusion-Convolutional Neural NetworksJames Atwood, Don Towsley. 1993-2001 [doi]
• Bayesian latent structure discovery from multi-neuron recordingsScott W. Linderman, Ryan P. Adams, Jonathan W. Pillow. 2002-2010 [doi]
• A Probabilistic Programming Approach To Probabilistic Data AnalysisFeras Saad, Vikash K. Mansinghka. 2011-2019 [doi]
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• Coordinate-wise Power MethodQi Lei, Kai Zhong, Inderjit S. Dhillon. 2056-2064 [doi]
• Learning Influence Functions from Incomplete ObservationsXinran He, Ke Xu, David Kempe 0001, Yan Liu. 2065-2073 [doi]
• Learning Structured Sparsity in Deep Neural NetworksWei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, Hai Li. 2074-2082 [doi]
• Sample Complexity of Automated Mechanism DesignMaria-Florina Balcan, Tuomas Sandholm, Ellen Vitercik. 2083-2091 [doi]
• Short-Dot: Computing Large Linear Transforms Distributedly Using Coded Short Dot ProductsSanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover. 2092-2100 [doi]
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• Linear Contextual Bandits with KnapsacksShipra Agrawal, Nikhil R. Devanur. 3450-3458 [doi]
• Reconstructing Parameters of Spreading Models from Partial ObservationsAndrey Y. Lokhov. 3459-3467 [doi]
• Spatiotemporal Residual Networks for Video Action RecognitionChristoph Feichtenhofer, Axel Pinz, Richard P. Wildes. 3468-3476 [doi]
• Path-Normalized Optimization of Recurrent Neural Networks with ReLU ActivationsBehnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro. 3477-3485 [doi]
• Strategic Attentive Writer for Learning Macro-ActionsAlexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John Agapiou, Koray Kavukcuoglu. 3486-3494 [doi]
• The Limits of Learning with Missing DataBrian Bullins, Elad Hazan, Tomer Koren. 3495-3503 [doi]
• RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention MechanismEdward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, Walter F. Stewart. 3504-3512 [doi]
• Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear SmoothersVeeranjaneyulu Sadhanala, Yu-Xiang Wang, Ryan J. Tibshirani. 3513-3521 [doi]
• Community Detection on Evolving GraphsStefano Leonardi, Aris Anagnostopoulos, Jakub Lacki, Silvio Lattanzi, Mohammad Mahdian. 3522-3530 [doi]
• Online and Differentially-Private Tensor DecompositionYining Wang, Anima Anandkumar. 3531-3539 [doi]
• Dimension-Free Iteration Complexity of Finite Sum Optimization ProblemsYossi Arjevani, Ohad Shamir. 3540-3548 [doi]
• Towards Conceptual CompressionKarol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra. 3549-3557 [doi]
• Exact Recovery of Hard Thresholding PursuitXiao-Tong Yuan, Ping Li, Tong Zhang. 3558-3566 [doi]
• Data Programming: Creating Large Training Sets, QuicklyAlexander J. Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré. 3567-3575 [doi]
• Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes BackVitaly Feldman. 3576-3584 [doi]
• Dynamic matrix recovery from incomplete observations under an exact low-rank constraintLiangbei Xu, Mark A. Davenport. 3585-3593 [doi]
• Fast Distributed Submodular Cover: Public-Private Data SummarizationBaharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi. 3594-3602 [doi]
• Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker MethodsCristina Savin, Gasper Tkacik. 3603-3611 [doi]
• Lifelong Learning with Weighted Majority VotesAnastasia Pentina, Ruth Urner. 3612-3620 [doi]
• Scaling Memory-Augmented Neural Networks with Sparse Reads and WritesJack W. Rae, Jonathan J. Hunt, Ivo Danihelka, Timothy Harley, Andrew W. Senior, Gregory Wayne, Alex Graves, Tim Lillicrap. 3621-3629 [doi]
• Matching Networks for One Shot LearningOriol Vinyals, Charles Blundell, Tim Lillicrap, Koray Kavukcuoglu, Daan Wierstra. 3630-3638 [doi]
• Tight Complexity Bounds for Optimizing Composite ObjectivesBlake E. Woodworth, Nati Srebro. 3639-3647 [doi]
• Graphical Time Warping for Joint Alignment of Multiple CurvesYizhi Wang, David J. Miller 0001, Kira Poskanzer, Yue Wang, Lin Tian, Guoqiang Yu. 3648-3656 [doi]
• Unsupervised Risk Estimation Using Only Conditional Independence StructureJacob Steinhardt, Percy S. Liang. 3657-3665 [doi]
• MetaGrad: Multiple Learning Rates in Online LearningTim van Erven, Wouter M. Koolen. 3666-3674 [doi]
• Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic MotivationTejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum. 3675-3683 [doi]
• High Dimensional Structured Superposition ModelsQilong Gu, Arindam Banerjee. 3684-3692 [doi]
• Joint quantile regression in vector-valued RKHSsMaxime Sangnier, Olivier Fercoq, Florence d'Alché-Buc. 3693-3701 [doi]
• The Forget-me-not ProcessKieran Milan, Joel Veness, James E. Kirkpatrick, Michael H. Bowling, Anna Koop, Demis Hassabis. 3702-3710 [doi]
• Wasserstein Training of Restricted Boltzmann MachinesGrégoire Montavon, Klaus-Robert Müller, Marco Cuturi. 3711-3719 [doi]
• Communication-Optimal Distributed ClusteringJiecao Chen, He Sun, David P. Woodruff, Qin Zhang. 3720-3728 [doi]
• Probing the Compositionality of Intuitive FunctionsEric Schulz, Josh Tenenbaum, David K. Duvenaud, Maarten Speekenbrink, Samuel J. Gershman. 3729-3737 [doi]
• Ladder Variational AutoencodersCasper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, Ole Winther. 3738-3746 [doi]
• The Multiple Quantile Graphical ModelAlnur Ali, J. Zico Kolter, Ryan J. Tibshirani. 3747-3755 [doi]
• Threshold Learning for Optimal Decision MakingNathan F. Lepora. 3756-3764 [doi]
• Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICAAapo Hyvärinen, Hiroshi Morioka. 3765-3773 [doi]
• Can Active Memory Replace Attention?Lukasz Kaiser, Samy Bengio. 3774-3782 [doi]
• Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor LearningTaiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami. 3783-3791 [doi]
• The Product CutThomas Laurent 0001, James H. von Brecht, Xavier Bresson, Arthur Szlam. 3792-3800 [doi]
• Learning Sparse Gaussian Graphical Models with Overlapping BlocksMohammad Javad Hosseini, Su-In Lee. 3801-3809 [doi]
• Yggdrasil: An Optimized System for Training Deep Decision Trees at ScaleFiras Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet S. Talwalkar. 3810-3818 [doi]
• Average-case hardness of RIP certificationTengyao Wang, Quentin Berthet, Yaniv Plan. 3819-3827 [doi]
• A forward model at Purkinje cell synapses facilitates cerebellar anticipatory controlIvan Herreros, Xerxes D. Arsiwalla, Paul F. M. J. Verschure. 3828-3836 [doi]
• Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringMichaël Defferrard, Xavier Bresson, Pierre Vandergheynst. 3837-3845 [doi]
• CliqueCNN: Deep Unsupervised Exemplar LearningMiguel Ángel Bautista, Artsiom Sanakoyeu, Ekaterina Tikhoncheva, Björn Ommer. 3846-3854 [doi]
• Large-Scale Price Optimization via Network FlowShinji Ito, Ryohei Fujimaki. 3855-3863 [doi]
• Online Pricing with Strategic and Patient BuyersMichal Feldman, Tomer Koren, Roi Livni, Yishay Mansour, Aviv Zohar. 3864-3872 [doi]
• Global Optimality of Local Search for Low Rank Matrix RecoverySrinadh Bhojanapalli, Behnam Neyshabur, Nati Srebro. 3873-3881 [doi]
• Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based SequencesDaniel Neil, Michael Pfeiffer, Shih-Chii Liu. 3882-3890 [doi]
• Improving PAC Exploration Using the Median Of MeansJason Pazis, Ronald Parr, Jonathan P. How. 3891-3899 [doi]
• Infinite Hidden Semi-Markov Modulated Interaction Point ProcessMatt Zhang, Peng Lin, Peng Lin, Ting Guo, Yang Wang, Yang Wang, Fang Chen. 3900-3908 [doi]
• Cooperative Inverse Reinforcement LearningDylan Hadfield-Menell, Stuart J. Russell, Pieter Abbeel, Anca D. Dragan. 3909-3917 [doi]
• Spatio-Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic EnvironmentsRansalu Senanayake, Lionel Ott, Simon Timothy O'Callaghan, Fabio Tozeto Ramos. 3918-3926 [doi]
• Select-and-Sample for Spike-and-Slab Sparse CodingAbdul-Saboor Sheikh, Jörg Lücke. 3927-3935 [doi]
• Tractable Operations for Arithmetic Circuits of Probabilistic ModelsYujia Shen, Arthur Choi, Adnan Darwiche. 3936-3944 [doi]
• Greedy Feature ConstructionDino Oglic, Thomas Gärtner. 3945-3953 [doi]
• Mistake Bounds for Binary Matrix CompletionMark Herbster, Stephen Pasteris, Massimiliano Pontil. 3954-3962 [doi]
• Data driven estimation of Laplace-Beltrami operatorFrédéric Chazal, Ilaria Giulini, Bertrand Michel. 3963-3971 [doi]
• Tracking the Best Expert in Non-stationary Stochastic EnvironmentsChen-Yu Wei, Yi-Te Hong, Chi-Jen Lu. 3972-3980 [doi]
• Learning to learn by gradient descent by gradient descentMarcin Andrychowicz, Misha Denil, Sergio Gomez Colmenarejo, Matthew W. Hoffman, David Pfau, Tom Schaul, Nando de Freitas. 3981-3989 [doi]
• Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving ProcessesHassan A. Kingravi, Harshal R. Maske, Girish Chowdhary. 3990-3998 [doi]
• Quantum Perceptron ModelsAshish Kapoor, Nathan Wiebe, Krysta Marie Svore. 3999-4007 [doi]
• Guided Policy Search via Approximate Mirror DescentWilliam H. Montgomery, Sergey Levine. 4008-4016 [doi]
• The Power of Optimization from SamplesEric Balkanski, Aviad Rubinstein, Yaron Singer. 4017-4025 [doi]
• Deep Exploration via Bootstrapped DQNIan Osband, Charles Blundell, Alexander Pritzel, Benjamin Van Roy. 4026-4034 [doi]
• A Multi-step Inertial Forward-Backward Splitting Method for Non-convex OptimizationJingwei Liang, Jalal Fadili, Gabriel Peyré. 4035-4043 [doi]
• Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without MessagesYin Cheng Ng, Pawel M. Chilinski, Ricardo Silva. 4044-4052 [doi]
• Convolutional Neural FabricsShreyas Saxena, Jakob Verbeek. 4053-4061 [doi]
• Adaptive Newton Method for Empirical Risk Minimization to Statistical AccuracyAryan Mokhtari, Hadi Daneshmand, Aurélien Lucchi, Thomas Hofmann, Alejandro Ribeiro. 4062-4070 [doi]
• A Sparse Interactive Model for Matrix Completion with Side InformationJin Lu, Guannan Liang, Jiangwen Sun, Jinbo Bi. 4071-4079 [doi]
• Coresets for Scalable Bayesian Logistic RegressionJonathan H. Huggins, Trevor Campbell, Tamara Broderick. 4080-4088 [doi]
• Agnostic Estimation for Misspecified Phase Retrieval ModelsMatey Neykov, Zhaoran Wang, Han Liu. 4089-4097 [doi]
• Linear Relaxations for Finding Diverse Elements in Metric SpacesAditya Bhaskara, Mehrdad Ghadiri, Vahab S. Mirrokni, Ola Svensson. 4098-4106 [doi]
• Binarized Neural NetworksItay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, Yoshua Bengio. 4107-4115 [doi]
• Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic ConsequencesChi Jin, Yuchen Zhang, Sivaraman Balakrishnan, Martin J. Wainwright, Michael I. Jordan. 4116-4124 [doi]
• Memory-Efficient Backpropagation Through TimeAudrunas Gruslys, Rémi Munos, Ivo Danihelka, Marc Lanctot, Alex Graves. 4125-4133 [doi]
• Bayesian Optimization with Robust Bayesian Neural NetworksJost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter. 4134-4142 [doi]
• Learnable Visual MarkersOleg Grinchuk, Vadim Lebedev, Victor S. Lempitsky. 4143-4151 [doi]
• Fast Algorithms for Robust PCA via Gradient DescentXinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis. 4152-4160 [doi]
• One-vs-Each Approximation to Softmax for Scalable Estimation of ProbabilitiesMichalis K. Titsias. 4161-4169 [doi]
• Learning Deep Embeddings with Histogram LossEvgeniya Ustinova, Victor S. Lempitsky. 4170-4178 [doi]
• Spectral Learning of Dynamic Systems from Nonequilibrium DataHao Wu, Frank Noé. 4179-4187 [doi]
• Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained SamplingChengtao Li, Suvrit Sra, Stefanie Jegelka. 4188-4196 [doi]
• Mapping Estimation for Discrete Optimal TransportMichaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard. 4197-4205 [doi]
• Batched Gaussian Process Bandit Optimization via Determinantal Point ProcessesTarun Kathuria, Amit Deshpande, Pushmeet Kohli. 4206-4214 [doi]
• Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued imagesVladimir Golkov, Marcin J. Skwark, Antonij Golkov, Alexey Dosovitskiy, Thomas Brox, Jens Meiler, Daniel Cremers. 4215-4223 [doi]
• Linear Feature Encoding for Reinforcement LearningZhao Song, Ronald E. Parr, Xuejun Liao, Lawrence Carin. 4224-4232 [doi]
• A Minimax Approach to Supervised LearningFarzan Farnia, David Tse. 4233-4241 [doi]
• Edge-exchangeable graphs and sparsityDiana Cai, Trevor Campbell, Tamara Broderick. 4242-4250 [doi]
• A Locally Adaptive Normal DistributionGeorgios Arvanitidis, Lars Kai Hansen, Søren Hauberg. 4251-4259 [doi]
• Completely random measures for modelling block-structured sparse networksTue Herlau, Mikkel N. Schmidt, Morten Mørup. 4260-4268 [doi]
• Sparse Support Recovery with Non-smooth Loss FunctionsKévin Degraux, Gabriel Peyré, Jalal Fadili, Laurent Jacques. 4269-4277 [doi]
• Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity StatisticsTravis Monk, Cristina Savin, Jörg Lücke. 4278-4286 [doi]
• Learning values across many orders of magnitudeHado P. van Hasselt, Arthur Guez, Matteo Hessel, Volodymyr Mnih, David Silver. 4287-4295 [doi]
• Adaptive Smoothed Online Multi-Task LearningKeerthiram Murugesan, Hanxiao Liu, Jaime G. Carbonell, Yiming Yang. 4296-4304 [doi]
• Safe Exploration in Finite Markov Decision Processes with Gaussian ProcessesMatteo Turchetta, Felix Berkenkamp, Andreas Krause 0001. 4305-4313 [doi]
• Probabilistic Linear Multistep MethodsOnur Teymur, Konstantinos Zygalakis, Ben Calderhead. 4314-4321 [doi]
• Stochastic Three-Composite Convex MinimizationAlp Yurtsever, Bang Công Vu, Volkan Cevher. 4322-4330 [doi]
• Using Fast Weights to Attend to the Recent PastJimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu. 4331-4339 [doi]
• Maximal Sparsity with Deep Networks?Bo Xin, Yizhou Wang, Wen Gao 0001, David P. Wipf, Baoyuan Wang. 4340-4348 [doi]
• Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word EmbeddingsTolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, Adam Tauman Kalai. 4349-4357 [doi]
• beta-risk: a New Surrogate Risk for Learning from Weakly Labeled DataValentina Zantedeschi, Rémi Emonet, Marc Sebban. 4358-4366 [doi]
• Learning Additive Exponential Family Graphical Models via \ell_{2, 1}-norm Regularized M-EstimationXiao-Tong Yuan, Ping Li, Tong Zhang, Qingshan Liu, Guangcan Liu. 4367-4375 [doi]
• Backprop KF: Learning Discriminative Deterministic State EstimatorsTuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel. 4376-4384 [doi]
• LightRNN: Memory and Computation-Efficient Recurrent Neural NetworksXiang Li, Tao Qin, Jian Yang, Xiaolin Hu, Tie-Yan Liu. 4385-4393 [doi]
• Fast recovery from a union of subspacesChinmay Hegde, Piotr Indyk, Ludwig Schmidt. 4394-4402 [doi]
• Incremental Variational Sparse Gaussian Process RegressionChing-An Cheng, Byron Boots. 4403-4411 [doi]
• A Consistent Regularization Approach for Structured PredictionCarlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi. 4412-4420 [doi]
• Clustering Signed Networks with the Geometric Mean of LaplaciansPedro Mercado, Francesco Tudisco, Matthias Hein 0001. 4421-4429 [doi]
• An urn model for majority voting in classification ensemblesVíctor Soto, Alberto Suárez, Gonzalo Martínez-Muñoz. 4430-4438 [doi]
• Avoiding Imposters and Delinquents: Adversarial Crowdsourcing and Peer PredictionJacob Steinhardt, Gregory Valiant, Moses Charikar. 4439-4447 [doi]
• Fast and accurate spike sorting of high-channel count probes with KiloSortMarius Pachitariu, Nicholas A. Steinmetz, Shabnam N. Kadir, Matteo Carandini, Kenneth D. Harris. 4448-4456 [doi]
• Combining Adversarial Guarantees and Stochastic Fast Rates in Online LearningWouter M. Koolen, Peter Grünwald, Tim van Erven. 4457-4465 [doi]
• Ancestral Causal InferenceSara Magliacane, Tom Claassen, Joris M. Mooij. 4466-4474 [doi]
• More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised LearningXinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu. 4475-4483 [doi]
• Tagger: Deep Unsupervised Perceptual GroupingKlaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber. 4484-4492 [doi]
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• Interaction Networks for Learning about Objects, Relations and PhysicsPeter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, Koray Kavukcuoglu. 4502-4510 [doi]
• Efficient state-space modularization for planning: theory, behavioral and neural signaturesDaniel McNamee, Daniel M. Wolpert, Máte Lengyel. 4511-4519 [doi]
• Provable Efficient Online Matrix Completion via Non-convex Stochastic Gradient DescentChi Jin, Sham M. Kakade, Praneeth Netrapalli. 4520-4528 [doi]
• Online Bayesian Moment Matching for Topic Modeling with Unknown Number of TopicsWei-Shou Hsu, Pascal Poupart. 4529-4537 [doi]
• Computing and maximizing influence in linear threshold and triggering modelsJustin T. Khim, Varun Jog, Po-Ling Loh. 4538-4546 [doi]
• Coevolutionary Latent Feature Processes for Continuous-Time User-Item InteractionsYichen Wang, Nan Du, Rakshit Trivedi, Le Song. 4547-4555 [doi]
• Optimal Learning for Multi-pass Stochastic Gradient MethodsJunhong Lin, Lorenzo Rosasco. 4556-4564 [doi]
• Generative Adversarial Imitation LearningJonathan Ho, Stefano Ermon. 4565-4573 [doi]
• Latent Attention For If-Then Program SynthesisChang Liu, Xinyun Chen, Eui Chul Richard Shin, Mingcheng Chen, Dawn Xiaodong Song. 4574-4582 [doi]
• Dual Space Gradient Descent for Online LearningTrung Le, Tu Nguyen, Vu Nguyen, Dinh Q. Phung. 4583-4591 [doi]
• Riemannian SVRG: Fast Stochastic Optimization on Riemannian ManifoldsHongyi Zhang, Sashank J. Reddi, Suvrit Sra. 4592-4600 [doi]
• Professor Forcing: A New Algorithm for Training Recurrent NetworksAnirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio. 4601-4609 [doi]
• Learning brain regions via large-scale online structured sparse dictionary learningElvis Dohmatob, Arthur Mensch, Gaël Varoquaux, Bertrand Thirion. 4610-4618 [doi]
• Efficient Neural Codes under Metabolic ConstraintsZhuo Wang, Xue-Xin Wei, Alan A. Stocker, Daniel D. Lee. 4619-4627 [doi]
• Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methodsAndrej Risteski, Yuanzhi Li. 4628-4636 [doi]
• Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual InformationAlexander Shishkin, Anastasia A. Bezzubtseva, Alexey Drutsa, Ilia Shishkov, Ekaterina Gladkikh, Gleb Gusev, Pavel Serdyukov. 4637-4645 [doi]
• Bayesian Intermittent Demand Forecasting for Large InventoriesMatthias W. Seeger, David Salinas, Valentin Flunkert. 4646-4654 [doi]
• Visual Question Answering with Question Representation Update (QRU)Ruiyu Li, Jiaya Jia. 4655-4663 [doi]
• Learning Parametric Sparse Models for Image Super-ResolutionYongbo Li, Weisheng Dong, Xuemei Xie, Guangming Shi, Xin Li, Donglai Xu. 4664-4672 [doi]
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• Asynchronous Parallel Greedy Coordinate DescentYang You, Xiangru Lian, Ji Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, James Demmel, Cho-Jui Hsieh. 4682-4690 [doi]
• Iterative Refinement of the Approximate Posterior for Directed Belief NetworksDevon R. Hjelm, Ruslan Salakhutdinov, KyungHyun Cho, Nebojsa Jojic, Vince D. Calhoun, Junyoung Chung. 4691-4699 [doi]
• Assortment Optimization Under the Mallows modelAntoine Désir, Vineet Goyal, Srikanth Jagabathula, Danny Segev. 4700-4708 [doi]
• Disease Trajectory MapsPeter Schulam, Raman Arora. 4709-4717 [doi]
• Multistage Campaigning in Social NetworksMehrdad Farajtabar, Xiaojing Ye, Sahar Harati, Le Song, Hongyuan Zha. 4718-4726 [doi]
• Learning in Games: Robustness of Fast ConvergenceDylan J. Foster, Zhiyuan Li, Thodoris Lykouris, Karthik Sridharan, Éva Tardos. 4727-4735 [doi]
• Improving Variational Autoencoders with Inverse Autoregressive FlowDiederik P. Kingma, Tim Salimans, Rafal Józefowicz, Xi Chen, Xi Chen, Ilya Sutskever, Max Welling. 4736-4744 [doi]
• Algorithms and matching lower bounds for approximately-convex optimizationAndrej Risteski, Yuanzhi Li. 4745-4753 [doi]
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• Kernel Bayesian Inference with Posterior RegularizationYang Song, Jun Zhu, Yong Ren. 4763-4771 [doi]
• Neural Universal Discrete DenoiserTaesup Moon, Seonwoo Min, Byunghan Lee, Sungroh Yoon. 4772-4780 [doi]
• Optimal Architectures in a Solvable Model of Deep NetworksJonathan Kadmon, Haim Sompolinsky. 4781-4789 [doi]
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• Supervised Learning with Tensor NetworksEdwin Stoudenmire, David J. Schwab. 4799-4807 [doi]
• Multi-step learning and underlying structure in statistical modelsMaia Fraser. 4808-4816 [doi]
• Structure-Blind Signal RecoveryDmitry Ostrovsky, Zaïd Harchaoui, Anatoli Juditsky, Arkadi Nemirovski. 4817-4825 [doi]
• An Architecture for Deep, Hierarchical Generative ModelsPhilip Bachman. 4826-4834 [doi]
• Feature selection in functional data classification with recursive maxima huntingJosé L. Torrecilla, Alberto Suárez. 4835-4843 [doi]
• Achieving budget-optimality with adaptive schemes in crowdsourcingAshish Khetan, Sewoong Oh. 4844-4852 [doi]
• Near-Optimal Smoothing of Structured Conditional Probability MatricesMoein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky. 4853-4861 [doi]
• Supervised Word Mover's DistanceGao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger. 4862-4870 [doi]
• Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block ModelsAmin Jalali 0002, Qiyang Han, Ioana Dumitriu, Maryam Fazel. 4871-4879 [doi]
• Full-Capacity Unitary Recurrent Neural NetworksScott Wisdom, Thomas Powers, John R. Hershey, Jonathan Le Roux, Les E. Atlas. 4880-4888 [doi]
• Threshold Bandits, With and Without Censored FeedbackJacob D. Abernethy, Kareem Amin, Ruihao Zhu. 4889-4897 [doi]
• Understanding the Effective Receptive Field in Deep Convolutional Neural NetworksWenjie Luo, Yujia Li, Raquel Urtasun, Richard S. Zemel. 4898-4906 [doi]
• Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization MethodsLev Bogolubsky, Pavel Dvurechensky, Alexander Gasnikov, Gleb Gusev, Yurii Nesterov, Andrei M. Raigorodskii, Aleksey Tikhonov, Maksim Zhukovskii. 4907-4915 [doi]
• k*-Nearest Neighbors: From Global to LocalOren Anava, Kfir Levy. 4916-4924 [doi]
• Normalized Spectral Map SynchronizationYanyao Shen, Qixing Huang, Nati Srebro, Sujay Sanghavi. 4925-4933 [doi]
• Beyond Exchangeability: The Chinese Voting ProcessMoontae Lee, Seok Hyun Jin, David M. Mimno. 4934-4942 [doi]
• A posteriori error bounds for joint matrix decomposition problemsNicolò Colombo, Nikos Vlassis. 4943-4950 [doi]
• A Bayesian method for reducing bias in neural representational similarity analysisMingbo Cai, Nicolas W. Schuck, Jonathan W. Pillow, Yael Niv. 4952-4960 [doi]
• Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion ProcessesChris Junchi Li, Zhaoran Wang, Han Liu. 4961-4969 [doi]
• Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other RegularitiesRuitong Huang, Tor Lattimore, András György, Csaba Szepesvári. 4970-4978 [doi]
• SDP Relaxation with Randomized Rounding for Energy DisaggregationKiarash Shaloudegi, András György, Csaba Szepesvári, Wilsun Xu. 4979-4987 [doi]
• Recovery Guarantee of Non-negative Matrix Factorization via Alternating UpdatesYuanzhi Li, Yingyu Liang, Andrej Risteski. 4988-4996 [doi]
• Unsupervised Learning of 3D Structure from ImagesDanilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, Nicolas Heess. 4997-5005 [doi]
• Poisson-Gamma dynamical systemsAaron Schein, Hanna M. Wallach, Mingyuan Zhou. 5006-5014 [doi]
• Gaussian Processes for Survival AnalysisTamara Fernandez, Nicolas Rivera, Yee Whye Teh. 5015-5023 [doi]
• Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output DomainIan En-Hsu Yen, Xiangru Huang, Kai Zhong, Ruohan Zhang, Pradeep Ravikumar, Inderjit S. Dhillon. 5024-5032 [doi]
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• Disentangling factors of variation in deep representation using adversarial trainingMichaël Mathieu, Junbo Jake Zhao, Pablo Sprechmann, Aditya Ramesh, Yann LeCun. 5041-5049 [doi]
• A primal-dual method for conic constrained distributed optimization problemsNecdet Serhat Aybat, Erfan Yazdandoost Hamedani. 5050-5058 [doi]
• Fundamental Limits of Budget-Fidelity Trade-off in Label CrowdsourcingFarshad Lahouti, Babak Hassibi. 5059-5067 [doi]
• An Online Sequence-to-Sequence Model Using Partial ConditioningNavdeep Jaitly, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, David Sussillo, Samy Bengio. 5067-5075 [doi]
• Learning Deep Parsimonious RepresentationsRenjie Liao, Alexander G. Schwing, Richard S. Zemel, Raquel Urtasun. 5076-5084 [doi]