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ICML2017

  • Massil Achab, Emmanuel Bacry, Stéphane Gaı̈ffas, Iacopo Mastromatteo, Jean-François Muzy. "Uncovering Causality from Multivariate Hawkes Integrated Cumulants" | [Home Page] | [PDF]

  • Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh. "A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions" | [Home Page] | [PDF]

  • Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel. "Constrained Policy Optimization" | [Home Page] | [PDF]

  • Naman Agarwal, Karan Singh. "The Price of Differential Privacy for Online Learning" | [Home Page] | [PDF]

  • Riad Akrour, Dmitry Sorokin, Jan Peters, Gerhard Neumann. "Local Bayesian Optimization of Motor Skills" | [Home Page] | [PDF]

  • Cem Aksoylar, Lorenzo Orecchia, Venkatesh Saligrama. "Connected Subgraph Detection with Mirror Descent on SDPs" | [Home Page] | [PDF]

  • Ahmed M. Alaa, Scott Hu, Mihaela Schaar. "Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis" | [Home Page] | [PDF]

  • Alnur Ali, Eric Wong, J. Zico Kolter. "A Semismooth Newton Method for Fast, Generic Convex Programming" | [Home Page] | [PDF]

  • Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, Charles Sutton. "Learning Continuous Semantic Representations of Symbolic Expressions" | [Home Page] | [PDF]

  • Zeyuan Allen-Zhu. "Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter" | [Home Page] | [PDF]

  • Zeyuan Allen-Zhu, Yuanzhi Li. "Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition" | [Home Page] | [PDF]

  • Zeyuan Allen-Zhu, Yuanzhi Li. "Faster Principal Component Regression and Stable Matrix Chebyshev Approximation" | [Home Page] | [PDF]

  • Zeyuan Allen-Zhu, Yuanzhi Li. "Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU" | [Home Page] | [PDF]

  • Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang. "Near-Optimal Design of Experiments via Regret Minimization" | [Home Page] | [PDF]

  • Brandon Amos, J. Zico Kolter. "OptNet: Differentiable Optimization as a Layer in Neural Networks" | [Home Page] | [PDF]

  • Brandon Amos, Lei Xu, J. Zico Kolter. "Input Convex Neural Networks" | [Home Page] | [PDF]

  • David Anderson, Ming Gu. "An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation" | [Home Page] | [PDF]

  • Jacob Andreas, Dan Klein, Sergey Levine. "Modular Multitask Reinforcement Learning with Policy Sketches" | [Home Page] | [PDF]

  • Oron Anschel, Nir Baram, Nahum Shimkin. "Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning" | [Home Page] | [PDF]

  • Ron Appel, Pietro Perona. "A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency" | [Home Page] | [PDF]

  • Sercan Ö. Arık, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi. "Deep Voice: Real-time Neural Text-to-Speech" | [Home Page] | [PDF]

  • Yossi Arjevani, Ohad Shamir. "Oracle Complexity of Second-Order Methods for Finite-Sum Problems" | [Home Page] | [PDF]

  • Martin Arjovsky, Soumith Chintala, Léon Bottou. "Wasserstein Generative Adversarial Networks" | [Home Page] | [PDF]

  • Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang. "Generalization and Equilibrium in Generative Adversarial Nets (GANs)" | [Home Page] | [PDF]

  • Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien. "A Closer Look at Memorization in Deep Networks" | [Home Page] | [PDF]

  • Kavosh Asadi, Michael L. Littman. "An Alternative Softmax Operator for Reinforcement Learning" | [Home Page] | [PDF]

  • Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh. "Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees" | [Home Page] | [PDF]

  • Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos. "Minimax Regret Bounds for Reinforcement Learning" | [Home Page] | [PDF]

  • Stephen H. Bach, Bryan He, Alexander Ratner, Christopher Ré. "Learning the Structure of Generative Models without Labeled Data" | [Home Page] | [PDF]

  • Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause. "Uniform Deviation Bounds for k-Means Clustering" | [Home Page] | [PDF]

  • Olivier Bachem, Mario Lucic, Andreas Krause. "Distributed and Provably Good Seedings for k-Means in Constant Rounds" | [Home Page] | [PDF]

  • Philip Bachman, Alessandro Sordoni, Adam Trischler. "Learning Algorithms for Active Learning" | [Home Page] | [PDF]

  • Arturs Backurs, Christos Tzamos. "Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms" | [Home Page] | [PDF]

  • Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang. "Differentially Private Clustering in High-Dimensional Euclidean Spaces" | [Home Page] | [PDF]

  • David Balduzzi. "Strongly-Typed Agents are Guaranteed to Interact Safely" | [Home Page] | [PDF]

  • David Balduzzi, Marcus Frean, Lennox Leary, J. P. Lewis, Kurt Wan-Duo Ma, Brian McWilliams. "The Shattered Gradients Problem: If resnets are the answer, then what is the question?" | [Home Page] | [PDF]

  • David Balduzzi, Brian McWilliams, Tony Butler-Yeoman. "Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks" | [Home Page] | [PDF]

  • Borja Balle, Odalric-Ambrym Maillard. "Spectral Learning from a Single Trajectory under Finite-State Policies" | [Home Page] | [PDF]

  • Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller. "Lost Relatives of the Gumbel Trick" | [Home Page] | [PDF]

  • Robert Bamler, Stephan Mandt. "Dynamic Word Embeddings" | [Home Page] | [PDF]

  • Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor. "End-to-End Differentiable Adversarial Imitation Learning" | [Home Page] | [PDF]

  • Andreas Bärmann, Sebastian Pokutta, Oskar Schneider. "Emulating the Expert: Inverse Optimization through Online Learning" | [Home Page] | [PDF]

  • Christopher Beckham, Christopher Pal. "Unimodal Probability Distributions for Deep Ordinal Classification" | [Home Page] | [PDF]

  • Jean-Michel Begon, Arnaud Joly, Pierre Geurts. "Globally Induced Forest: A Prepruning Compression Scheme" | [Home Page] | [PDF]

  • David Belanger, Bishan Yang, Andrew McCallum. "End-to-End Learning for Structured Prediction Energy Networks" | [Home Page] | [PDF]

  • Eugene Belilovsky, Kyle Kastner, Gael Varoquaux, Matthew B. Blaschko. "Learning to Discover Sparse Graphical Models" | [Home Page] | [PDF]

  • Marc G. Bellemare, Will Dabney, Rémi Munos. "A Distributional Perspective on Reinforcement Learning" | [Home Page] | [PDF]

  • Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc V. Le. "Neural Optimizer Search with Reinforcement Learning" | [Home Page] | [PDF]

  • Urs Bergmann, Nikolay Jetchev, Roland Vollgraf. "Learning Texture Manifolds with the Periodic Spatial GAN" | [Home Page] | [PDF]

  • Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay, Gerome Miklau. "Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models" | [Home Page] | [PDF]

  • Alina Beygelzimer, Francesco Orabona, Chicheng Zhang. "Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret" | [Home Page] | [PDF]

  • Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek. "Guarantees for Greedy Maximization of Non-submodular Functions with Applications" | [Home Page] | [PDF]

  • Ilija Bogunovic, Slobodan Mitrović, Jonathan Scarlett, Volkan Cevher. "Robust Submodular Maximization: A Non-Uniform Partitioning Approach" | [Home Page] | [PDF]

  • Piotr Bojanowski, Armand Joulin. "Unsupervised Learning by Predicting Noise" | [Home Page] | [PDF]

  • Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama. "Adaptive Neural Networks for Efficient Inference" | [Home Page] | [PDF]

  • Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis. "Compressed Sensing using Generative Models" | [Home Page] | [PDF]

  • Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky, Sebastian Riedel. "Programming with a Differentiable Forth Interpreter" | [Home Page] | [PDF]

  • Aleksandar Botev, Hippolyt Ritter, David Barber. "Practical Gauss-Newton Optimisation for Deep Learning" | [Home Page] | [PDF]

  • Gábor Braun, Sebastian Pokutta, Daniel Zink. "Lazifying Conditional Gradient Algorithms" | [Home Page] | [PDF]

  • Vladimir Braverman, Gereon Frahling, Harry Lang, Christian Sohler, Lin F. Yang. "Clustering High Dimensional Dynamic Data Streams" | [Home Page] | [PDF]

  • François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark Girolami. "On the Sampling Problem for Kernel Quadrature" | [Home Page] | [PDF]

  • Noam Brown, Tuomas Sandholm. "Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning" | [Home Page] | [PDF]

  • Alon Brutzkus, Amir Globerson. "Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs" | [Home Page] | [PDF]

  • David Budden, Alexander Matveev, Shibani Santurkar, Shraman Ray Chaudhuri, Nir Shavit. "Deep Tensor Convolution on Multicores" | [Home Page] | [PDF]

  • Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Shie Mannor. "Multi-objective Bandits: Optimizing the Generalized Gini Index" | [Home Page] | [PDF]

  • Bryan Cai, Constantinos Daskalakis, Gautam Kamath. "Priv’IT: Private and Sample Efficient Identity Testing" | [Home Page] | [PDF]

  • Daniele Calandriello, Alessandro Lazaric, Michal Valko. "Second-Order Kernel Online Convex Optimization with Adaptive Sketching" | [Home Page] | [PDF]

  • Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford. "“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions" | [Home Page] | [PDF]

  • Mathieu Carrière, Marco Cuturi, Steve Oudot. "Sliced Wasserstein Kernel for Persistence Diagrams" | [Home Page] | [PDF]

  • Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy. "Multiple Clustering Views from Multiple Uncertain Experts" | [Home Page] | [PDF]

  • Aditya Chaudhry, Pan Xu, Quanquan Gu. "Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference" | [Home Page] | [PDF]

  • Kamalika Chaudhuri, Prateek Jain, Nagarajan Natarajan. "Active Heteroscedastic Regression" | [Home Page] | [PDF]

  • Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav Sukhatme, Stefan Schaal, Sergey Levine. "Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning" | [Home Page] | [PDF]

  • Sheng Chen, Arindam Banerjee. "Robust Structured Estimation with Single-Index Models" | [Home Page] | [PDF]

  • Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou. "Adaptive Multiple-Arm Identification" | [Home Page] | [PDF]

  • Bangrui Chen, Peter I. Frazier. "Dueling Bandits with Weak Regret" | [Home Page] | [PDF]

  • Yichen Chen, Dongdong Ge, Mengdi Wang, Zizhuo Wang, Yinyu Ye, Hao Yin. "Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions" | [Home Page] | [PDF]

  • Yutian Chen, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick, Nando Freitas. "Learning to Learn without Gradient Descent by Gradient Descent" | [Home Page] | [PDF]

  • Bryant Chen, Daniel Kumor, Elias Bareinboim. "Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables" | [Home Page] | [PDF]

  • Xixian Chen, Michael R. Lyu, Irwin King. "Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data" | [Home Page] | [PDF]

  • Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao. "Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability" | [Home Page] | [PDF]

  • Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng. "Learning to Aggregate Ordinal Labels by Maximizing Separating Width" | [Home Page] | [PDF]

  • Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain. "Nearly Optimal Robust Matrix Completion" | [Home Page] | [PDF]

  • Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff. "Algorithms for $\ell_p$ Low-Rank Approximation" | [Home Page] | [PDF]

  • Minsik Cho, Daniel Brand. "MEC: Memory-efficient Convolution for Deep Neural Network" | [Home Page] | [PDF]

  • Arthur Choi, Adnan Darwiche. "On Relaxing Determinism in Arithmetic Circuits" | [Home Page] | [PDF]

  • Po-Wei Chou, Daniel Maturana, Sebastian Scherer. "Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution" | [Home Page] | [PDF]

  • Sayak Ray Chowdhury, Aditya Gopalan. "On Kernelized Multi-armed Bandits" | [Home Page] | [PDF]

  • Moustapha Cisse, Piotr Bojanowski, Edouard Grave, Yann Dauphin, Nicolas Usunier. "Parseval Networks: Improving Robustness to Adversarial Examples" | [Home Page] | [PDF]

  • Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou. "Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC" | [Home Page] | [PDF]

  • Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, Scott Yang. "AdaNet: Adaptive Structural Learning of Artificial Neural Networks" | [Home Page] | [PDF]

  • Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, Maurizio Filippone. "Random Feature Expansions for Deep Gaussian Processes" | [Home Page] | [PDF]

  • Marco Cuturi, Mathieu Blondel. "Soft-DTW: a Differentiable Loss Function for Time-Series" | [Home Page] | [PDF]

  • Wojciech Marian Czarnecki, Grzegorz Świrszcz, Max Jaderberg, Simon Osindero, Oriol Vinyals, Koray Kavukcuoglu. "Understanding Synthetic Gradients and Decoupled Neural Interfaces" | [Home Page] | [PDF]

  • Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song. "Stochastic Generative Hashing" | [Home Page] | [PDF]

  • Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro. "Logarithmic Time One-Against-Some" | [Home Page] | [PDF]

  • Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier. "Language Modeling with Gated Convolutional Networks" | [Home Page] | [PDF]

  • Colin Reimer Dawson, Chaofan Huang, Clayton T. Morrison. "An Infinite Hidden Markov Model With Similarity-Biased Transitions" | [Home Page] | [PDF]

  • Erik A. Daxberger, Bryan Kian Hsiang Low. "Distributed Batch Gaussian Process Optimization" | [Home Page] | [PDF]

  • Krzysztof Dembczyński, Wojciech Kotłowski, Oluwasanmi Koyejo, Nagarajan Natarajan. "Consistency Analysis for Binary Classification Revisited" | [Home Page] | [PDF]

  • Walter H. Dempsey, Alexander Moreno, Christy K. Scott, Michael L. Dennis, David H. Gustafson, Susan A. Murphy, James M. Rehg. "iSurvive: An Interpretable, Event-time Prediction Model for mHealth" | [Home Page] | [PDF]

  • Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, Alexander M. Rush. "Image-to-Markup Generation with Coarse-to-Fine Attention" | [Home Page] | [PDF]

  • Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, Pushmeet Kohli. "RobustFill: Neural Program Learning under Noisy I/O" | [Home Page] | [PDF]

  • Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart. "Being Robust (in High Dimensions) Can Be Practical" | [Home Page] | [PDF]

  • Vu Dinh, Arman Bilge, Cheng Zhang, Frederick A. Matsen IV. "Probabilistic Path Hamiltonian Monte Carlo" | [Home Page] | [PDF]

  • Laurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua Bengio. "Sharp Minima Can Generalize For Deep Nets" | [Home Page] | [PDF]

  • Justin Domke. "A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI" | [Home Page] | [PDF]

  • Chris Donahue, Zachary C. Lipton, Julian McAuley. "Dance Dance Convolution" | [Home Page] | [PDF]

  • Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou. "Stochastic Variance Reduction Methods for Policy Evaluation" | [Home Page] | [PDF]

  • Jonathan Eckstein, Noam Goldberg, Ai Kagawa. "Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement" | [Home Page] | [PDF]

  • Jesse Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Mohammad Norouzi, Douglas Eck, Karen Simonyan. "Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders" | [Home Page] | [PDF]

  • Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso. "Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening" | [Home Page] | [PDF]

  • Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh. "Maximum Selection and Ranking under Noisy Comparisons" | [Home Page] | [PDF]

  • Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias Khalil, Shuang Li, Le Song, Hongyuan Zha. "Fake News Mitigation via Point Process Based Intervention" | [Home Page] | [PDF]

  • Gabriele Farina, Christian Kroer, Tuomas Sandholm. "Regret Minimization in Behaviorally-Constrained Zero-Sum Games" | [Home Page] | [PDF]

  • Dan Feldman, Sedat Ozer, Daniela Rus. "Coresets for Vector Summarization with Applications to Network Graphs" | [Home Page] | [PDF]

  • Chelsea Finn, Pieter Abbeel, Sergey Levine. "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks" | [Home Page] | [PDF]

  • Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein, Jan Chorowski, David Sussillo. "Input Switched Affine Networks: An RNN Architecture Designed for Interpretability" | [Home Page] | [PDF]

  • Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson. "Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning" | [Home Page] | [PDF]

  • Andrew Forney, Judea Pearl, Elias Bareinboim. "Counterfactual Data-Fusion for Online Reinforcement Learners" | [Home Page] | [PDF]

  • Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil. "Forward and Reverse Gradient-Based Hyperparameter Optimization" | [Home Page] | [PDF]

  • Joseph Futoma, Sanjay Hariharan, Katherine Heller. "Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier" | [Home Page] | [PDF]

  • Yarin Gal, Riashat Islam, Zoubin Ghahramani. "Deep Bayesian Active Learning with Image Data" | [Home Page] | [PDF]

  • Tian Gao, Kshitij Fadnis, Murray Campbell. "Local-to-Global Bayesian Network Structure Learning" | [Home Page] | [PDF]

  • Dan Garber, Ohad Shamir, Nathan Srebro. "Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis" | [Home Page] | [PDF]

  • Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow. "Differentiable Programs with Neural Libraries" | [Home Page] | [PDF]

  • Guillaume Gautier, Rémi Bardenet, Michal Valko. "Zonotope Hit-and-run for Efficient Sampling from Projection DPPs" | [Home Page] | [PDF]

  • Rong Ge, Chi Jin, Yi Zheng. "No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis" | [Home Page] | [PDF]

  • Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin. "Convolutional Sequence to Sequence Learning" | [Home Page] | [PDF]

  • Claudio Gentile, Shuai Li, Purushottam Kar, Alexandros Karatzoglou, Giovanni Zappella, Evans Etrue. "On Context-Dependent Clustering of Bandits" | [Home Page] | [PDF]

  • Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, George E. Dahl. "Neural Message Passing for Quantum Chemistry" | [Home Page] | [PDF]

  • Tom Goldstein, Christoph Studer. "Convex Phase Retrieval without Lifting via PhaseMax" | [Home Page] | [PDF]

  • Javier González, Zhenwen Dai, Andreas Damianou, Neil D. Lawrence. "Preferential Bayesian Optimization" | [Home Page] | [PDF]

  • Jackson Gorham, Lester Mackey. "Measuring Sample Quality with Kernels" | [Home Page] | [PDF]

  • Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou. "Efficient softmax approximation for GPUs" | [Home Page] | [PDF]

  • Alex Graves, Marc G. Bellemare, Jacob Menick, Rémi Munos, Koray Kavukcuoglu. "Automated Curriculum Learning for Neural Networks" | [Home Page] | [PDF]

  • Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger. "On Calibration of Modern Neural Networks" | [Home Page] | [PDF]

  • Chirag Gupta, Arun Sai Suggala, Ankit Goyal, Harsha Vardhan Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain. "ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices" | [Home Page] | [PDF]

  • Michael Gygli, Mohammad Norouzi, Anelia Angelova. "Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs" | [Home Page] | [PDF]

  • Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine. "Reinforcement Learning with Deep Energy-Based Policies" | [Home Page] | [PDF]

  • Gaëtan Hadjeres, François Pachet, Frank Nielsen. "DeepBach: a Steerable Model for Bach Chorales Generation" | [Home Page] | [PDF]

  • Assaf Hallak, Shie Mannor. "Consistent On-Line Off-Policy Evaluation" | [Home Page] | [PDF]

  • Insu Han, Prabhanjan Kambadur, Kyoungsoo Park, Jinwoo Shin. "Faster Greedy MAP Inference for Determinantal Point Processes" | [Home Page] | [PDF]

  • Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum. "Data-Efficient Policy Evaluation Through Behavior Policy Search" | [Home Page] | [PDF]

  • Mehrtash Harandi, Mathieu Salzmann, Richard Hartley. "Joint Dimensionality Reduction and Metric Learning: A Geometric Take" | [Home Page] | [PDF]

  • Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy. "Deep IV: A Flexible Approach for Counterfactual Prediction" | [Home Page] | [PDF]

  • Avinatan Hassidim, Yaron Singer. "Robust Guarantees of Stochastic Greedy Algorithms" | [Home Page] | [PDF]

  • Elad Hazan, Karan Singh, Cyril Zhang. "Efficient Regret Minimization in Non-Convex Games" | [Home Page] | [PDF]

  • Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin. "Kernelized Support Tensor Machines" | [Home Page] | [PDF]

  • Reinhard Heckel, Kannan Ramchandran. "The Sample Complexity of Online One-Class Collaborative Filtering" | [Home Page] | [PDF]

  • João F. Henriques, Andrea Vedaldi. "Warped Convolutions: Efficient Invariance to Spatial Transformations" | [Home Page] | [PDF]

  • José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik. "Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space" | [Home Page] | [PDF]

  • Irina Higgins, Arka Pal, Andrei Rusu, Loic Matthey, Christopher Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner. "DARLA: Improving Zero-Shot Transfer in Reinforcement Learning" | [Home Page] | [PDF]

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  • Dor Levy, Lior Wolf. "Learning to Align the Source Code to the Compiled Object Code" | [Home Page] | [PDF]

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  • Marlos C. Machado, Marc G. Bellemare, Michael Bowling. "A Laplacian Framework for Option Discovery in Reinforcement Learning" | [Home Page] | [PDF]

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  • Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti. "On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations" | [Home Page] | [PDF]

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  • Lucas Maystre, Matthias Grossglauser. "Just Sort It! A Simple and Effective Approach to Active Preference Learning" | [Home Page] | [PDF]

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  • Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White. "Adapting Kernel Representations Online Using Submodular Maximization" | [Home Page] | [PDF]

  • Daniel Selsam, Percy Liang, David L. Dill. "Developing Bug-Free Machine Learning Systems With Formal Mathematics" | [Home Page] | [PDF]

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  • Shai Shalev-Shwartz, Ohad Shamir, Shaked Shammah. "Failures of Gradient-Based Deep Learning" | [Home Page] | [PDF]

  • Uri Shalit, Fredrik D. Johansson, David Sontag. "Estimating individual treatment effect: generalization bounds and algorithms" | [Home Page] | [PDF]

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  • Vatsal Sharan, Gregory Valiant. "Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use" | [Home Page] | [PDF]

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  • Jaehong Yoon, Sung Ju Hwang. "Combined Group and Exclusive Sparsity for Deep Neural Networks" | [Home Page] | [PDF]

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  • Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin. "Stochastic Gradient Monomial Gamma Sampler" | [Home Page] | [PDF]

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  • Chenzi Zhang, Shuguang Hu, Zhihao Gavin Tang, T-H. Hubert Chan. "Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method" | [Home Page] | [PDF]

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  • Yuchen Zhang, Percy Liang, Martin J. Wainwright. "Convexified Convolutional Neural Networks" | [Home Page] | [PDF]

  • Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang. "Projection-free Distributed Online Learning in Networks" | [Home Page] | [PDF]

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  • Shengjia Zhao, Jiaming Song, Stefano Ermon. "Learning Hierarchical Features from Deep Generative Models" | [Home Page] | [PDF]

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  • Chaoxu Zhou, Wenbo Gao, Donald Goldfarb. "Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values" | [Home Page] | [PDF]

  • Yichi Zhou, Jialian Li, Jun Zhu. "Identify the Nash Equilibrium in Static Games with Random Payoffs" | [Home Page] | [PDF]

  • Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh. "When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications" | [Home Page] | [PDF]

  • Rongda Zhu, Lingxiao Wang, Chengxiang Zhai, Quanquan Gu. "High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm" | [Home Page] | [PDF]

  • Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnı́k, Jürgen Schmidhuber. "Recurrent Highway Networks" | [Home Page] | [PDF]

  • Masrour Zoghi, Tomas Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvari, Zheng Wen. "Online Learning to Rank in Stochastic Click Models" | [Home Page] | [PDF]