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Editors: Doina Precup, Yee Whye Teh
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Uncovering Causality from Multivariate Hawkes Integrated Cumulants
; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1-10
A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions
Jayadev Acharya, Hirakendu Das, Alon Orlitsky, Ananda Theertha Suresh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:11-21
Constrained Policy Optimization
Joshua Achiam, David Held, Aviv Tamar, Pieter Abbeel; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:22-31
The Price of Differential Privacy for Online Learning
Naman Agarwal, Karan Singh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:32-40
Local Bayesian Optimization of Motor Skills
Riad Akrour, Dmitry Sorokin, Jan Peters, Gerhard Neumann; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:41-50
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Connected Subgraph Detection with Mirror Descent on SDPs
Cem Aksoylar, Lorenzo Orecchia, Venkatesh Saligrama; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:51-59
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis
Ahmed M. Alaa, Scott Hu, Mihaela Schaar; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:60-69
A Semismooth Newton Method for Fast, Generic Convex Programming
Alnur Ali, Eric Wong, J. Zico Kolter; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:70-79
Learning Continuous Semantic Representations of Symbolic Expressions
Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli, Charles Sutton; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:80-88
Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter
Zeyuan Allen-Zhu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:89-97
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Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Zeyuan Allen-Zhu, Yuanzhi Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:98-106
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Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
Zeyuan Allen-Zhu, Yuanzhi Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:107-115
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Follow the Compressed Leader: Faster Online Learning of Eigenvectors and Faster MMWU
Zeyuan Allen-Zhu, Yuanzhi Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:116-125
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Near-Optimal Design of Experiments via Regret Minimization
Zeyuan Allen-Zhu, Yuanzhi Li, Aarti Singh, Yining Wang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:126-135
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OptNet: Differentiable Optimization as a Layer in Neural Networks
Brandon Amos, J. Zico Kolter; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:136-145
Input Convex Neural Networks
Brandon Amos, Lei Xu, J. Zico Kolter; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:146-155
An Efficient, Sparsity-Preserving, Online Algorithm for Low-Rank Approximation
David Anderson, Ming Gu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:156-165
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas, Dan Klein, Sergey Levine; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:166-175
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning
Oron Anschel, Nir Baram, Nahum Shimkin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:176-185
A Simple Multi-Class Boosting Framework with Theoretical Guarantees and Empirical Proficiency
Ron Appel, Pietro Perona; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:186-194
Deep Voice: Real-time Neural Text-to-Speech
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; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:195-204
Oracle Complexity of Second-Order Methods for Finite-Sum Problems
Yossi Arjevani, Ohad Shamir; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:205-213
Wasserstein Generative Adversarial Networks
Martin Arjovsky, Soumith Chintala, Léon Bottou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:214-223
Generalization and Equilibrium in Generative Adversarial Nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:224-232
A Closer Look at Memorization in Deep Networks
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:233-242
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An Alternative Softmax Operator for Reinforcement Learning
Kavosh Asadi, Michael L. Littman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:243-252
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Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:253-262
Minimax Regret Bounds for Reinforcement Learning
Mohammad Gheshlaghi Azar, Ian Osband, Rémi Munos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:263-272
Learning the Structure of Generative Models without Labeled Data
Stephen H. Bach, Bryan He, Alexander Ratner, Christopher Ré; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:273-282
Uniform Deviation Bounds for k-Means Clustering
Olivier Bachem, Mario Lucic, S. Hamed Hassani, Andreas Krause; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:283-291
Distributed and Provably Good Seedings for k-Means in Constant Rounds
Olivier Bachem, Mario Lucic, Andreas Krause; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:292-300
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Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:301-310
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Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms
Arturs Backurs, Christos Tzamos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:311-321
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Maria-Florina Balcan, Travis Dick, Yingyu Liang, Wenlong Mou, Hongyang Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:322-331
Strongly-Typed Agents are Guaranteed to Interact Safely
David Balduzzi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:332-341
The Shattered Gradients Problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary, J. P. Lewis, Kurt Wan-Duo Ma, Brian McWilliams; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:342-350
Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks
David Balduzzi, Brian McWilliams, Tony Butler-Yeoman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:351-360
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja Balle, Odalric-Ambrym Maillard; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:361-370
Lost Relatives of the Gumbel Trick
Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:371-379
Dynamic Word Embeddings
Robert Bamler, Stephan Mandt; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:380-389
End-to-End Differentiable Adversarial Imitation Learning
Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:390-399
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Emulating the Expert: Inverse Optimization through Online Learning
Andreas Bärmann, Sebastian Pokutta, Oskar Schneider; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:400-410
Unimodal Probability Distributions for Deep Ordinal Classification
Christopher Beckham, Christopher Pal; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:411-419
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Globally Induced Forest: A Prepruning Compression Scheme
Jean-Michel Begon, Arnaud Joly, Pierre Geurts; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:420-428
End-to-End Learning for Structured Prediction Energy Networks
David Belanger, Bishan Yang, Andrew McCallum; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:429-439
Learning to Discover Sparse Graphical Models
Eugene Belilovsky, Kyle Kastner, Gael Varoquaux, Matthew B. Blaschko; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:440-448
A Distributional Perspective on Reinforcement Learning
Marc G. Bellemare, Will Dabney, Rémi Munos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:449-458
Neural Optimizer Search with Reinforcement Learning
Irwan Bello, Barret Zoph, Vijay Vasudevan, Quoc V. Le; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:459-468
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Learning Texture Manifolds with the Periodic Spatial GAN
Urs Bergmann, Nikolay Jetchev, Roland Vollgraf; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:469-477
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Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay, Gerome Miklau; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:478-487
Efficient Online Bandit Multiclass Learning with $\tilde{O}(\sqrt{T})$ Regret
Alina Beygelzimer, Francesco Orabona, Chicheng Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:488-497
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:498-507
Robust Submodular Maximization: A Non-Uniform Partitioning Approach
Ilija Bogunovic, Slobodan Mitrović, Jonathan Scarlett, Volkan Cevher; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:508-516
Unsupervised Learning by Predicting Noise
Piotr Bojanowski, Armand Joulin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:517-526
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Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi, Joseph Wang, Ofer Dekel, Venkatesh Saligrama; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:527-536
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Compressed Sensing using Generative Models
Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:537-546
Programming with a Differentiable Forth Interpreter
Matko Bošnjak, Tim Rocktäschel, Jason Naradowsky, Sebastian Riedel; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:547-556
Practical Gauss-Newton Optimisation for Deep Learning
Aleksandar Botev, Hippolyt Ritter, David Barber; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:557-565
Lazifying Conditional Gradient Algorithms
Gábor Braun, Sebastian Pokutta, Daniel Zink; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:566-575
Clustering High Dimensional Dynamic Data Streams
Vladimir Braverman, Gereon Frahling, Harry Lang, Christian Sohler, Lin F. Yang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:576-585
On the Sampling Problem for Kernel Quadrature
François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark Girolami; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:586-595
Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning
Noam Brown, Tuomas Sandholm; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:596-604
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus, Amir Globerson; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:605-614
Deep Tensor Convolution on Multicores
David Budden, Alexander Matveev, Shibani Santurkar, Shraman Ray Chaudhuri, Nir Shavit; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:615-624
Multi-objective Bandits: Optimizing the Generalized Gini Index
Róbert Busa-Fekete, Balázs Szörényi, Paul Weng, Shie Mannor; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:625-634
Priv’IT: Private and Sample Efficient Identity Testing
Bryan Cai, Constantinos Daskalakis, Gautam Kamath; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:635-644
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello, Alessandro Lazaric, Michal Valko; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:645-653
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions
Yair Carmon, John C. Duchi, Oliver Hinder, Aaron Sidford; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:654-663
Sliced Wasserstein Kernel for Persistence Diagrams
Mathieu Carrière, Marco Cuturi, Steve Oudot; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:664-673
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Multiple Clustering Views from Multiple Uncertain Experts
Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:674-683
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference
Aditya Chaudhry, Pan Xu, Quanquan Gu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:684-693
Active Heteroscedastic Regression
Kamalika Chaudhuri, Prateek Jain, Nagarajan Natarajan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:694-702
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning
Yevgen Chebotar, Karol Hausman, Marvin Zhang, Gaurav Sukhatme, Stefan Schaal, Sergey Levine; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:703-711
Robust Structured Estimation with Single-Index Models
Sheng Chen, Arindam Banerjee; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:712-721
Adaptive Multiple-Arm Identification
Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:722-730
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Dueling Bandits with Weak Regret
Bangrui Chen, Peter I. Frazier; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:731-739
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions
Yichen Chen, Dongdong Ge, Mengdi Wang, Zizhuo Wang, Yinyu Ye, Hao Yin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:740-747
Learning to Learn without Gradient Descent by Gradient Descent
Yutian Chen, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Timothy P. Lillicrap, Matt Botvinick, Nando Freitas; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:748-756
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Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables
Bryant Chen, Daniel Kumor, Elias Bareinboim; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:757-766
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Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data
Xixian Chen, Michael R. Lyu, Irwin King; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:767-776
Online Partial Least Square Optimization: Dropping Convexity for Better Efficiency and Scalability
Zhehui Chen, Lin F. Yang, Chris Junchi Li, Tuo Zhao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:777-786
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:787-796
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Nearly Optimal Robust Matrix Completion
Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:797-805
Algorithms for $\ell_p$ Low-Rank Approximation
Flavio Chierichetti, Sreenivas Gollapudi, Ravi Kumar, Silvio Lattanzi, Rina Panigrahy, David P. Woodruff; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:806-814
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MEC: Memory-efficient Convolution for Deep Neural Network
Minsik Cho, Daniel Brand; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:815-824
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On Relaxing Determinism in Arithmetic Circuits
Arthur Choi, Adnan Darwiche; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:825-833
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Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution
Po-Wei Chou, Daniel Maturana, Sebastian Scherer; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:834-843
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury, Aditya Gopalan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:844-853
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cisse, Piotr Bojanowski, Edouard Grave, Yann Dauphin, Nicolas Usunier; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:854-863
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Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong, Bo Chen, Hongwei Liu, Mingyuan Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:864-873
AdaNet: Adaptive Structural Learning of Artificial Neural Networks
Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, Scott Yang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:874-883
Random Feature Expansions for Deep Gaussian Processes
Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, Maurizio Filippone; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:884-893
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi, Mathieu Blondel; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:894-903
Understanding Synthetic Gradients and Decoupled Neural Interfaces
Wojciech Marian Czarnecki, Grzegorz Świrszcz, Max Jaderberg, Simon Osindero, Oriol Vinyals, Koray Kavukcuoglu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:904-912
Stochastic Generative Hashing
Bo Dai, Ruiqi Guo, Sanjiv Kumar, Niao He, Le Song; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:913-922
Logarithmic Time One-Against-Some
Hal Daumé III, Nikos Karampatziakis, John Langford, Paul Mineiro; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:923-932
Language Modeling with Gated Convolutional Networks
Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:933-941
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An Infinite Hidden Markov Model With Similarity-Biased Transitions
Colin Reimer Dawson, Chaofan Huang, Clayton T. Morrison; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:942-950
Distributed Batch Gaussian Process Optimization
Erik A. Daxberger, Bryan Kian Hsiang Low; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:951-960
Consistency Analysis for Binary Classification Revisited
Krzysztof Dembczyński, Wojciech Kotłowski, Oluwasanmi Koyejo, Nagarajan Natarajan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:961-969
iSurvive: An Interpretable, Event-time Prediction Model for mHealth
Walter H. Dempsey, Alexander Moreno, Christy K. Scott, Michael L. Dennis, David H. Gustafson, Susan A. Murphy, James M. Rehg; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:970-979
Image-to-Markup Generation with Coarse-to-Fine Attention
Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, Alexander M. Rush; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:980-989
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RobustFill: Neural Program Learning under Noisy I/O
Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed, Pushmeet Kohli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:990-998
Being Robust (in High Dimensions) Can Be Practical
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Ankur Moitra, Alistair Stewart; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:999-1008
Probabilistic Path Hamiltonian Monte Carlo
Vu Dinh, Arman Bilge, Cheng Zhang, Frederick A. Matsen IV; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1009-1018
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua Bengio; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1019-1028
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI
Justin Domke; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1029-1038
Dance Dance Convolution
Chris Donahue, Zachary C. Lipton, Julian McAuley; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1039-1048
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Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li, Lin Xiao, Dengyong Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1049-1058
Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Jonathan Eckstein, Noam Goldberg, Ai Kagawa; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1059-1067
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Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Jesse Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Mohammad Norouzi, Douglas Eck, Karen Simonyan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1068-1077
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Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1078-1087
Maximum Selection and Ranking under Noisy Comparisons
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1088-1096
Fake News Mitigation via Point Process Based Intervention
Mehrdad Farajtabar, Jiachen Yang, Xiaojing Ye, Huan Xu, Rakshit Trivedi, Elias Khalil, Shuang Li, Le Song, Hongyuan Zha; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1097-1106
Regret Minimization in Behaviorally-Constrained Zero-Sum Games
Gabriele Farina, Christian Kroer, Tuomas Sandholm; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1107-1116
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Coresets for Vector Summarization with Applications to Network Graphs
Dan Feldman, Sedat Ozer, Daniela Rus; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1117-1125
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Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn, Pieter Abbeel, Sergey Levine; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1126-1135
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
Jakob N. Foerster, Justin Gilmer, Jascha Sohl-Dickstein, Jan Chorowski, David Sussillo; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1136-1145
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Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster, Nantas Nardelli, Gregory Farquhar, Triantafyllos Afouras, Philip H. S. Torr, Pushmeet Kohli, Shimon Whiteson; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1146-1155
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Counterfactual Data-Fusion for Online Reinforcement Learners
Andrew Forney, Judea Pearl, Elias Bareinboim; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1156-1164
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi, Michele Donini, Paolo Frasconi, Massimiliano Pontil; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1165-1173
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
Joseph Futoma, Sanjay Hariharan, Katherine Heller; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1174-1182
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Deep Bayesian Active Learning with Image Data
Yarin Gal, Riashat Islam, Zoubin Ghahramani; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1183-1192
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Local-to-Global Bayesian Network Structure Learning
Tian Gao, Kshitij Fadnis, Murray Campbell; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1193-1202
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Communication-efficient Algorithms for Distributed Stochastic Principal Component Analysis
Dan Garber, Ohad Shamir, Nathan Srebro; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1203-1212
Differentiable Programs with Neural Libraries
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1213-1222
Zonotope Hit-and-run for Efficient Sampling from Projection DPPs
Guillaume Gautier, Rémi Bardenet, Michal Valko; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1223-1232
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis
Rong Ge, Chi Jin, Yi Zheng; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1233-1242
Convolutional Sequence to Sequence Learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1243-1252
On Context-Dependent Clustering of Bandits
Claudio Gentile, Shuai Li, Purushottam Kar, Alexandros Karatzoglou, Giovanni Zappella, Evans Etrue; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1253-1262
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Neural Message Passing for Quantum Chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, George E. Dahl; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1263-1272
Convex Phase Retrieval without Lifting via PhaseMax
Tom Goldstein, Christoph Studer; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1273-1281
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Preferential Bayesian Optimization
Javier González, Zhenwen Dai, Andreas Damianou, Neil D. Lawrence; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1282-1291
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Measuring Sample Quality with Kernels
Jackson Gorham, Lester Mackey; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1292-1301
Efficient softmax approximation for GPUs
Grave, Armand Joulin, Moustapha Cissé, David Grangier, Hervé Jégou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1302-1310
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Automated Curriculum Learning for Neural Networks
Alex Graves, Marc G. Bellemare, Jacob Menick, Rémi Munos, Koray Kavukcuoglu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1311-1320
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On Calibration of Modern Neural Networks
Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1321-1330
ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices
Chirag Gupta, Arun Sai Suggala, Ankit Goyal, Harsha Vardhan Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1331-1340
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
Michael Gygli, Mohammad Norouzi, Anelia Angelova; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1341-1351
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Reinforcement Learning with Deep Energy-Based Policies
Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, Sergey Levine; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1352-1361
DeepBach: a Steerable Model for Bach Chorales Generation
Gaëtan Hadjeres, François Pachet, Frank Nielsen; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1362-1371
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Consistent On-Line Off-Policy Evaluation
Assaf Hallak, Shie Mannor; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1372-1383
Faster Greedy MAP Inference for Determinantal Point Processes
Insu Han, Prabhanjan Kambadur, Kyoungsoo Park, Jinwoo Shin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1384-1393
Data-Efficient Policy Evaluation Through Behavior Policy Search
Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1394-1403
Joint Dimensionality Reduction and Metric Learning: A Geometric Take
Mehrtash Harandi, Mathieu Salzmann, Richard Hartley; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1404-1413
Deep IV: A Flexible Approach for Counterfactual Prediction
Jason Hartford, Greg Lewis, Kevin Leyton-Brown, Matt Taddy; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1414-1423
Robust Guarantees of Stochastic Greedy Algorithms
Avinatan Hassidim, Yaron Singer; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1424-1432
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Efficient Regret Minimization in Non-Convex Games
Elad Hazan, Karan Singh, Cyril Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1433-1441
Kernelized Support Tensor Machines
Lifang He, Chun-Ta Lu, Guixiang Ma, Shen Wang, Linlin Shen, Philip S. Yu, Ann B. Ragin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1442-1451
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The Sample Complexity of Online One-Class Collaborative Filtering
Reinhard Heckel, Kannan Ramchandran; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1452-1460
Warped Convolutions: Efficient Invariance to Spatial Transformations
João F. Henriques, Andrea Vedaldi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1461-1469
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Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Space
José Miguel Hernández-Lobato, James Requeima, Edward O. Pyzer-Knapp, Alán Aspuru-Guzik; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1470-1479
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DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
Irina Higgins, Arka Pal, Andrei Rusu, Loic Matthey, Christopher Burgess, Alexander Pritzel, Matthew Botvinick, Charles Blundell, Alexander Lerchner; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1480-1490
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Jun-ichiro Hirayama, Aapo Hyvärinen, Motoaki Kawanabe; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1491-1500
Multilevel Clustering via Wasserstein Means
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1501-1509
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Matthew D. Hoffman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1510-1519
Minimizing Trust Leaks for Robust Sybil Detection
János Höner, Shinichi Nakajima, Alexander Bauer, Klaus-Robert Müller, Nico Görnitz; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1520-1528
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
Mingyi Hong, Davood Hajinezhad, Ming-Min Zhao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1529-1538
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
Andrea Horňáková, Jan-Hendrik Lange, Bjoern Andres; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1539-1548
Dissipativity Theory for Nesterov’s Accelerated Method
Bin Hu, Laurent Lessard; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1549-1557
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1558-1567
State-Frequency Memory Recurrent Neural Networks
Hao Hu, Guo-Jun Qi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1568-1577
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Deep Generative Models for Relational Data with Side Information
Changwei Hu, Piyush Rai, Lawrence Carin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1578-1586
Toward Controlled Generation of Text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1587-1596
Tensor Decomposition with Smoothness
Masaaki Imaizumi, Kohei Hayashi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1597-1606
Variational Inference for Sparse and Undirected Models
John Ingraham, Debora Marks; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1607-1616
Fairness in Reinforcement Learning
Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, Aaron Roth; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1617-1626
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero, Oriol Vinyals, Alex Graves, David Silver, Koray Kavukcuoglu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1627-1635
Scalable Generative Models for Multi-label Learning with Missing Labels
Vikas Jain, Nirbhay Modhe, Piyush Rai; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1636-1644
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Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1645-1654
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Bayesian Optimization with Tree-structured Dependencies
Rodolphe Jenatton, Cedric Archambeau, Javier González, Matthias Seeger; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1655-1664
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite, Anna Choromanska, David Sontag; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1665-1674
From Patches to Images: A Nonparametric Generative Model
Geng Ji, Michael C. Hughes, Erik B. Sudderth; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1675-1683
Density Level Set Estimation on Manifolds with DBSCAN
Heinrich Jiang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1684-1693
Uniform Convergence Rates for Kernel Density Estimation
Heinrich Jiang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1694-1703
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1704-1713
Efficient Nonmyopic Active Search
Shali Jiang, Gustavo Malkomes, Geoff Converse, Alyssa Shofner, Benjamin Moseley, Roman Garnett; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1714-1723
How to Escape Saddle Points Efficiently
Chi Jin, Rong Ge, Praneeth Netrapalli, Sham M. Kakade, Michael I. Jordan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1724-1732
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljačić; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1733-1741
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An Adaptive Test of Independence with Analytic Kernel Embeddings
Wittawat Jitkrittum, Zoltán Szabó, Arthur Gretton; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1742-1751
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Tyler B. Johnson, Carlos Guestrin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1752-1760
Differentially Private Chi-squared Test by Unit Circle Mechanism
Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1761-1770
Video Pixel Networks
Nal Kalchbrenner, Aäron Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, Koray Kavukcuoglu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1771-1779
Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP
Satyen Kale, Zohar Karnin, Tengyuan Liang, Dávid Pál; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1780-1788
Recursive Partitioning for Personalization using Observational Data
Nathan Kallus; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1789-1798
Multi-fidelity Bayesian Optimisation with Continuous Approximations
Kirthevasan Kandasamy, Gautam Dasarathy, Jeff Schneider, Barnabás Póczos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1799-1808
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky, Tom Silver, David A. Mély, Mohamed Eldawy, Miguel Lázaro-Gredilla, Xinghua Lou, Nimrod Dorfman, Szymon Sidor, Scott Phoenix, Dileep George; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1809-1818
Learning in POMDPs with Monte Carlo Tree Search
Sammie Katt, Frans A. Oliehoek, Christopher Amato; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1819-1827
Meritocratic Fairness for Cross-Population Selection
Michael Kearns, Aaron Roth, Zhiwei Steven Wu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1828-1836
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On Approximation Guarantees for Greedy Low Rank Optimization
Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Joydeep Ghosh, Sahand Negahban; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1837-1846
Graph-based Isometry Invariant Representation Learning
Renata Khasanova, Pascal Frossard; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1847-1856
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jung Kwon Lee, Jiwon Kim; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1857-1865
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Juyong Kim, Yookoon Park, Gunhee Kim, Sung Ju Hwang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1866-1874
Cost-Optimal Learning of Causal Graphs
Murat Kocaoglu, Alex Dimakis, Sriram Vishwanath; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1875-1884
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh, Percy Liang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1885-1894
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Moritz Kohler, Aurelien Lucchi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1895-1904
PixelCNN Models with Auxiliary Variables for Natural Image Modeling
Alexander Kolesnikov, Christoph H. Lampert; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1905-1914
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Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daumé III, John Langford; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1915-1924
Evaluating Bayesian Models with Posterior Dispersion Indices
Alp Kucukelbir, Yixin Wang, David M. Blei; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1925-1934
Resource-efficient Machine Learning in 2 KB RAM for the Internet of Things
Ashish Kumar, Saurabh Goyal, Manik Varma; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1935-1944
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Grammar Variational Autoencoder
Matt J. Kusner, Brooks Paige, José Miguel Hernández-Lobato; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1945-1954
Co-clustering through Optimal Transport
Charlotte Laclau, Ievgen Redko, Basarab Matei, Younès Bennani, Vincent Brault; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1955-1964
Conditional Accelerated Lazy Stochastic Gradient Descent
Guanghui Lan, Sebastian Pokutta, Yi Zhou, Daniel Zink; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1965-1974
Consistent k-Clustering
Silvio Lattanzi, Sergei Vassilvitskii; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1975-1984
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Deep Spectral Clustering Learning
Marc T. Law, Raquel Urtasun, Richard S. Zemel; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1985-1994
Coordinated Multi-Agent Imitation Learning
Hoang M. Le, Yisong Yue, Peter Carr, Patrick Lucey; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:1995-2003
Bayesian inference on random simple graphs with power law degree distributions
Juho Lee, Creighton Heaukulani, Zoubin Ghahramani, Lancelot F. James, Seungjin Choi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2004-2013
Confident Multiple Choice Learning
Kimin Lee, Changho Hwang, KyoungSoo Park, Jinwoo Shin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2014-2023
Deriving Neural Architectures from Sequence and Graph Kernels
Tao Lei, Wengong Jin, Regina Barzilay, Tommi Jaakkola; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2024-2033
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Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu, Inderjit S. Dhillon, Pradeep Ravikumar; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2034-2042
Learning to Align the Source Code to the Compiled Object Code
Dor Levy, Lior Wolf; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2043-2051
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li, Yarin Gal; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2052-2061
Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations
Yuanzhi Li, Yingyu Liang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2062-2070
Provably Optimal Algorithms for Generalized Linear Contextual Bandits
Lihong Li, Yu Lu, Dengyong Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2071-2080
Fast k-Nearest Neighbour Search via Prioritized DCI
Ke Li, Jitendra Malik; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2081-2090
Forest-type Regression with General Losses and Robust Forest
Alexander Hanbo Li, Andrew Martin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2091-2100
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Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms
Qianxiao Li, Cheng Tai, Weinan E; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2101-2110
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization
Qunwei Li, Yi Zhou, Yingbin Liang, Pramod K. Varshney; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2111-2119
Exact MAP Inference by Avoiding Fractional Vertices
Erik M. Lindgren, Alexandros G. Dimakis, Adam Klivans; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2120-2129
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Leveraging Union of Subspace Structure to Improve Constrained Clustering
John Lipor, Laura Balzano; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2130-2139
Zero-Inflated Exponential Family Embeddings
Li-Ping Liu, David M. Blei; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2140-2148
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Iterative Machine Teaching
Weiyang Liu, Bo Dai, Ahmad Humayun, Charlene Tay, Chen Yu, Linda B. Smith, James M. Rehg, Le Song; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2149-2158
Algorithmic Stability and Hypothesis Complexity
Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2159-2167
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Analogical Inference for Multi-relational Embeddings
Hanxiao Liu, Yuexin Wu, Yiming Yang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2168-2178
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Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu, Xiao-Tong Yuan, Lezi Wang, Qingshan Liu, Dimitris N. Metaxas; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2179-2187
Gram-CTC: Automatic Unit Selection and Target Decomposition for Sequence Labelling
Hairong Liu, Zhenyao Zhu, Xiangang Li, Sanjeev Satheesh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2188-2197
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Learning Infinite Layer Networks Without the Kernel Trick
Roi Livni, Daniel Carmon, Amir Globerson; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2198-2207
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Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long, Han Zhu, Jianmin Wang, Michael I. Jordan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2208-2217
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Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
Christos Louizos, Max Welling; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2218-2227
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How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?
Andreas Loukas; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2228-2237
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Learning Deep Architectures via Generalized Whitened Neural Networks
Ping Luo; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2238-2246
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Learning Gradient Descent: Better Generalization and Longer Horizons
Kaifeng Lv, Shunhua Jiang, Jian Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2247-2255
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Spherical Structured Feature Maps for Kernel Approximation
Yueming Lyu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2256-2264
Stochastic Gradient MCMC Methods for Hidden Markov Models
Yi-An Ma, Nicholas J. Foti, Emily B. Fox; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2265-2274
Self-Paced Co-training
Fan Ma, Deyu Meng, Qi Xie, Zina Li, Xuanyi Dong; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2275-2284
Interactive Learning from Policy-Dependent Human Feedback
James MacGlashan, Mark K. Ho, Robert Loftin, Bei Peng, Guan Wang, David L. Roberts, Matthew E. Taylor, Michael L. Littman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2285-2294
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A Laplacian Framework for Option Discovery in Reinforcement Learning
Marlos C. Machado, Marc G. Bellemare, Michael Bowling; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2295-2304
Frame-based Data Factorizations
Sebastian Mair, Ahcène Boubekki, Ulf Brefeld; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2305-2313
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Global optimization of Lipschitz functions
Cédric Malherbe, Nicolas Vayatis; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2314-2323
On Mixed Memberships and Symmetric Nonnegative Matrix Factorizations
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2324-2333
Bayesian Models of Data Streams with Hierarchical Power Priors
Andrés Masegosa, Thomas D. Nielsen, Helge Langseth, Darı́o Ramos-López, Antonio Salmerón, Anders L. Madsen; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2334-2343
Just Sort It! A Simple and Effective Approach to Active Preference Learning
Lucas Maystre, Matthias Grossglauser; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2344-2353
ChoiceRank: Identifying Preferences from Node Traffic in Networks
Lucas Maystre, Matthias Grossglauser; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2354-2362
Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
Mason McGill, Pietro Perona; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2363-2372
Risk Bounds for Transferring Representations With and Without Fine-Tuning
Daniel McNamara, Maria-Florina Balcan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2373-2381
Nonnegative Matrix Factorization for Time Series Recovery From a Few Temporal Aggregates
Jiali Mei, Yohann De Castro, Yannig Goude, Georges Hébrail; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2382-2390
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Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks
Lars Mescheder, Sebastian Nowozin, Andreas Geiger; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2391-2400
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
Zakaria Mhammedi, Andrew Hellicar, Ashfaqur Rahman, James Bailey; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2401-2409
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao, Edward Grefenstette, Phil Blunsom; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2410-2419
Variational Boosting: Iteratively Refining Posterior Approximations
Andrew C. Miller, Nicholas J. Foti, Ryan P. Adams; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2420-2429
Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2430-2439
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Tight Bounds for Approximate Carathéodory and Beyond
Vahab Mirrokni, Renato Paes Leme, Adrian Vladu, Sam Chiu-wai Wong; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2440-2448
Deletion-Robust Submodular Maximization: Data Summarization with “the Right to be Forgotten”
Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2449-2458
Prediction and Control with Temporal Segment Models
Nikhil Mishra, Pieter Abbeel, Igor Mordatch; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2459-2468
Improving Gibbs Sampler Scan Quality with DoGS
Ioannis Mitliagkas, Lester Mackey; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2469-2477
Differentially Private Submodular Maximization: Data Summarization in Disguise
Marko Mitrovic, Mark Bun, Andreas Krause, Amin Karbasi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2478-2487
Active Learning for Top-$K$ Rank Aggregation from Noisy Comparisons
Soheil Mohajer, Changho Suh, Adel Elmahdy; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2488-2497
Variational Dropout Sparsifies Deep Neural Networks
Dmitry Molchanov, Arsenii Ashukha, Dmitry Vetrov; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2498-2507
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Regularising Non-linear Models Using Feature Side-information
Amina Mollaysa, Pablo Strasser, Alexandros Kalousis; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2508-2517
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou, Zhengdong Lu, Hang Li, Zhi Jin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2518-2526
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McGan: Mean and Covariance Feature Matching GAN
Youssef Mroueh, Tom Sercu, Vaibhava Goel; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2527-2535
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller, David Gifford, Tommi Jaakkola; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2536-2544
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
Mahesh Chandra Mukkamala, Matthias Hein; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2545-2553
Meta Networks
Tsendsuren Munkhdalai, Hong Yu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2554-2563
Understanding the Representation and Computation of Multilayer Perceptrons: A Case Study in Speech Recognition
Tasha Nagamine, Nima Mesgarani; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2564-2573
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Adaptive Sampling Probabilities for Non-Smooth Optimization
Hongseok Namkoong, Aman Sinha, Steve Yadlowsky, John C. Duchi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2574-2583
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil, Jun Haeng Lee, Tobi Delbruck, Shih-Chii Liu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2584-2593
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Post-Inference Prior Swapping
Willie Neiswanger, Eric Xing; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2594-2602
The Loss Surface of Deep and Wide Neural Networks
Quynh Nguyen, Matthias Hein; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2603-2612
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient
Lam M. Nguyen, Jie Liu, Katya Scheinberg, Martin Takáč; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2613-2621
Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data
Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2622-2631
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Multichannel End-to-end Speech Recognition
Tsubasa Ochiai, Shinji Watanabe, Takaaki Hori, John R. Hershey; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2632-2641
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Conditional Image Synthesis with Auxiliary Classifier GANs
Augustus Odena, Christopher Olah, Jonathon Shlens; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2642-2651
Nyström Method with Kernel K-means++ Samples as Landmarks
Dino Oglic, Thomas Gärtner; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2652-2660
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning
Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2661-2670
The Statistical Recurrent Unit
Junier B. Oliva, Barnabás Póczos, Jeff Schneider; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2671-2680
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Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2681-2690
Algebraic Variety Models for High-Rank Matrix Completion
Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2691-2700
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Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Ian Osband, Benjamin Van Roy; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2701-2710
Bidirectional Learning for Time-series Models with Hidden Units
Takayuki Osogami, Hiroshi Kajino, Taro Sekiyama; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2711-2720
Count-Based Exploration with Neural Density Models
Georg Ostrovski, Marc G. Bellemare, Aäron Oord, Rémi Munos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2721-2730
Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad, Farnood Salehi, Elisa Celis, Patrick Thiran, Michael Unser; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2731-2740
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Stochastic Bouncy Particle Sampler
Ari Pakman, Dar Gilboa, David Carlson, Liam Paninski; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2741-2750
A Birth-Death Process for Feature Allocation
Konstantina Palla, David Knowles, Zoubin Ghahramani; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2751-2759
Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control
Yunpeng Pan, Xinyan Yan, Evangelos A. Theodorou, Byron Boots; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2760-2768
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
Ashkan Panahi, Devdatt Dubhashi, Fredrik D. Johansson, Chiranjib Bhattacharyya; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2769-2777
Curiosity-driven Exploration by Self-supervised Prediction
Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2778-2787
Asynchronous Distributed Variational Gaussian Process for Regression
Hao Peng, Shandian Zhe, Xiao Zhang, Yuan Qi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2788-2797
Geometry of Neural Network Loss Surfaces via Random Matrix Theory
Jeffrey Pennington, Yasaman Bahri; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2798-2806
Multi-task Learning with Labeled and Unlabeled Tasks
Anastasia Pentina, Christoph H. Lampert; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2807-2816
Robust Adversarial Reinforcement Learning
Lerrel Pinto, James Davidson, Rahul Sukthankar, Abhinav Gupta; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2817-2826
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Neural Episodic Control
Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech Badia, Oriol Vinyals, Demis Hassabis, Daan Wierstra, Charles Blundell; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2827-2836
Online and Linear-Time Attention by Enforcing Monotonic Alignments
Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, Douglas Eck; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2837-2846
On the Expressive Power of Deep Neural Networks
Maithra Raghu, Ben Poole, Jon Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2847-2854
Estimating the unseen from multiple populations
Aditi Raghunathan, Gregory Valiant, James Zou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2855-2863
Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery
Mostafa Rahmani, George Atia; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2864-2873
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Innovation Pursuit: A New Approach to the Subspace Clustering Problem
Mostafa Rahmani, George Atia; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2874-2882
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High Dimensional Bayesian Optimization with Elastic Gaussian Process
Santu Rana, Cheng Li, Sunil Gupta, Vu Nguyen, Svetha Venkatesh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2883-2891
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Equivariance Through Parameter-Sharing
Siamak Ravanbakhsh, Jeff Schneider, Barnabás Póczos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2892-2901
Large-Scale Evolution of Image Classifiers
Esteban Real, Sherry Moore, Andrew Selle, Saurabh Saxena, Yutaka Leon Suematsu, Jie Tan, Quoc V. Le, Alexey Kurakin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2902-2911
Parallel Multiscale Autoregressive Density Estimation
Scott Reed, Aäron Oord, Nal Kalchbrenner, Sergio Gómez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, Nando Freitas; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2912-2921
Real-Time Adaptive Image Compression
Oren Rippel, Lubomir Bourdev; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2922-2930
Active Learning for Accurate Estimation of Linear Models
Carlos Riquelme, Mohammad Ghavamzadeh, Alessandro Lazaric; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2931-2939
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter, David G. T. Barrett, Adam Santoro, Matt M. Botvinick; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2940-2949
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Pain-Free Random Differential Privacy with Sensitivity Sampling
Benjamin I. P. Rubinstein, Francesco Aldà; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2950-2959
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Enumerating Distinct Decision Trees
Salvatore Ruggieri; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2960-2968
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Bayesian Boolean Matrix Factorisation
Tammo Rukat, Chris C. Holmes, Michalis K. Titsias, Christopher Yau; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2969-2978
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks
Itay Safran, Ohad Shamir; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2979-2987
Asymmetric Tri-training for Unsupervised Domain Adaptation
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2988-2997
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai, Marthinus Christoffel Plessis, Gang Niu, Masashi Sugiyama; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:2998-3006
Analytical Guarantees on Numerical Precision of Deep Neural Networks
Charbel Sakr, Yongjune Kim, Naresh Shanbhag; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3007-3016
Hierarchy Through Composition with Multitask LMDPs
Andrew M. Saxe, Adam C. Earle, Benjamin Rosman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3017-3026
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3027-3036
Adapting Kernel Representations Online Using Submodular Maximization
Matthew Schlegel, Yangchen Pan, Jiecao Chen, Martha White; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3037-3046
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Daniel Selsam, Percy Liang, David L. Dill; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3047-3056
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Identifying Best Interventions through Online Importance Sampling
Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3057-3066
Failures of Gradient-Based Deep Learning
Shai Shalev-Shwartz, Ohad Shamir, Shaked Shammah; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3067-3075
Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit, Fredrik D. Johansson, David Sontag; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3076-3085
Online Learning with Local Permutations and Delayed Feedback
Ohad Shamir, Liran Szlak; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3086-3094
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use
Vatsal Sharan, Gregory Valiant; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3095-3104
Differentially Private Ordinary Least Squares
Or Sheffet; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3105-3114
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit
Jie Shen, Ping Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3115-3124
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
Li Shen, Wei Liu, Ganzhao Yuan, Shiqian Ma; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3125-3134
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World of Bits: An Open-Domain Platform for Web-Based Agents
Tianlin Shi, Andrej Karpathy, Linxi Fan, Jonathan Hernandez, Percy Liang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3135-3144
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Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar, Peyton Greenside, Anshul Kundaje; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3145-3153
Optimal Densification for Fast and Accurate Minwise Hashing
Anshumali Shrivastava; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3154-3163
Bottleneck Conditional Density Estimation
Rui Shu, Hung H. Bui, Mohammad Ghavamzadeh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3164-3172
Attentive Recurrent Comparators
Pranav Shyam, Shubham Gupta, Ambedkar Dukkipati; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3173-3181
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Gradient Boosted Decision Trees for High Dimensional Sparse Output
Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3182-3190
The Predictron: End-To-End Learning and Planning
David Silver, Hado Hasselt, Matteo Hessel, Tom Schaul, Arthur Guez, Tim Harley, Gabriel Dulac-Arnold, David Reichert, Neil Rabinowitz, Andre Barreto, Thomas Degris; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3191-3199
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo
Umut Şimşekli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3200-3209
Nonparanormal Information Estimation
Shashank Singh, Barnabás Póczos; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3210-3219
High-Dimensional Structured Quantile Regression
Vidyashankar Sivakumar, Arindam Banerjee; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3220-3229
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Robust Budget Allocation via Continuous Submodular Functions
Matthew Staib, Stefanie Jegelka; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3230-3240
Probabilistic Submodular Maximization in Sub-Linear Time
Serban Stan, Morteza Zadimoghaddam, Andreas Krause, Amin Karbasi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3241-3250
Approximate Steepest Coordinate Descent
Sebastian U. Stich, Anant Raj, Martin Jaggi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3251-3259
Ordinal Graphical Models: A Tale of Two Approaches
Arun Sai Suggala, Eunho Yang, Pradeep Ravikumar; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3260-3269
Tensor Balancing on Statistical Manifold
Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3270-3279
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Safety-Aware Algorithms for Adversarial Contextual Bandit
Wen Sun, Debadeepta Dey, Ashish Kapoor; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3280-3288
Relative Fisher Information and Natural Gradient for Learning Large Modular Models
Ke Sun, Frank Nielsen; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3289-3298
meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
Xu Sun, Xuancheng Ren, Shuming Ma, Houfeng Wang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3299-3308
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Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew Bagnell; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3309-3318
Axiomatic Attribution for Deep Networks
Mukund Sundararajan, Ankur Taly, Qiqi Yan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3319-3328
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Distributed Mean Estimation with Limited Communication
Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3329-3337
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu, Koji Tsuda, Ichiro Takeuchi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3338-3347
Coherent Probabilistic Forecasts for Hierarchical Time Series
Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3348-3357
Partitioned Tensor Factorizations for Learning Mixed Membership Models
Zilong Tan, Sayan Mukherjee; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3358-3367
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Gradient Coding: Avoiding Stragglers in Distributed Learning
Rashish Tandon, Qi Lei, Alexandros G. Dimakis, Nikos Karampatziakis; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3368-3376
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares
Junqi Tang, Mohammad Golbabaee, Mike E. Davies; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3377-3386
Neural Networks and Rational Functions
Matus Telgarsky; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3387-3393
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification
Hoai An Le Thi, Hoai Minh Le, Duy Nhat Phan, Bach Tran; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3394-3403
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An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis
Yuandong Tian; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3404-3413
Evaluating the Variance of Likelihood-Ratio Gradient Estimators
Seiya Tokui, Issei Sato; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3414-3423
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3424-3433
Boosted Fitted Q-Iteration
Samuele Tosatto, Matteo Pirotta, Carlo D’Eramo, Marcello Restelli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3434-3443
Diameter-Based Active Learning
Christopher Tosh, Sanjoy Dasgupta; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3444-3452
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Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani, Richard Turner; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3453-3461
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3462-3471
Hyperplane Clustering via Dual Principal Component Pursuit
Manolis C. Tsakiris, René Vidal; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3472-3481
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Breaking Locality Accelerates Block Gauss-Seidel
Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3482-3491
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Multilabel Classification with Group Testing and Codes
Shashanka Ubaru, Arya Mazumdar; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3492-3501
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft, Sandra Hirche; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3502-3510
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Learning Determinantal Point Processes with Moments and Cycles
John Urschel, Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3511-3520
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Automatic Discovery of the Statistical Types of Variables in a Dataset
Isabel Valera, Zoubin Ghahramani; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3521-3529
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Model-Independent Online Learning for Influence Maximization
Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3530-3539
FeUdal Networks for Hierarchical Reinforcement Learning
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul, Nicolas Heess, Max Jaderberg, David Silver, Koray Kavukcuoglu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3540-3549
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo, Daniel Hernández-Lobato; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3550-3559
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, Honglak Lee; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3560-3569
On orthogonality and learning recurrent networks with long term dependencies
Eugene Vorontsov, Chiheb Trabelsi, Samuel Kadoury, Chris Pal; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3570-3578
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Fast Bayesian Intensity Estimation for the Permanental Process
Christian J. Walder, Adrian N. Bishop; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3579-3588
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudı́k; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3589-3597
Capacity Releasing Diffusion for Speed and Locality
Di Wang, Kimon Fountoulakis, Monika Henzinger, Michael W. Mahoney, Satish Rao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3598-3607
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3608-3616
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Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Lingxiao Wang, Quanquan Gu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3617-3626
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Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang, Stefanie Jegelka; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3627-3635
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3636-3645
Robust Probabilistic Modeling with Bayesian Data Reweighting
Yixin Wang, Alp Kucukelbir, David M. Blei; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3646-3655
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang, Chengtao Li, Stefanie Jegelka, Pushmeet Kohli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3656-3664
Tensor Decomposition via Simultaneous Power Iteration
Po-An Wang, Chi-Jen Lu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3665-3673
Sequence Modeling via Segmentations
Chong Wang, Yining Wang, Po-Sen Huang, Abdelrahman Mohamed, Dengyong Zhou, Li Deng; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3674-3683
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Variational Policy for Guiding Point Processes
Yichen Wang, Grady Williams, Evangelos Theodorou, Le Song; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3684-3693
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms
Jialei Wang, Lin Xiao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3694-3702
Beyond Filters: Compact Feature Map for Portable Deep Model
Yunhe Wang, Chang Xu, Chao Xu, Dacheng Tao; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3703-3711
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery
Lingxiao Wang, Xiao Zhang, Quanquan Gu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3712-3721
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
Pengfei Wei, Ramon Sagarna, Yiping Ke, Yew-Soon Ong, Chi-Keong Goh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3722-3731
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Latent Intention Dialogue Models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, Steve Young; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3732-3741
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Unifying Task Specification in Reinforcement Learning
Martha White; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3742-3750
Learned Optimizers that Scale and Generalize
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman, Sergio Gómez Colmenarejo, Misha Denil, Nando Freitas, Jascha Sohl-Dickstein; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3751-3760
Exact Inference for Integer Latent-Variable Models
Kevin Winner, Debora Sujono, Dan Sheldon; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3761-3770
Tensor Belief Propagation
Andrew Wrigley, Wee Sun Lee, Nan Ye; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3771-3779
A Unified View of Multi-Label Performance Measures
Xi-Zhu Wu, Zhi-Hua Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3780-3788
Dual Supervised Learning
Yingce Xia, Tao Qin, Wei Chen, Jiang Bian, Nenghai Yu, Tie-Yan Liu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3789-3798
Learning Latent Space Models with Angular Constraints
Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3799-3810
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Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Pengtao Xie, Aarti Singh, Eric P. Xing; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3811-3820
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Yi Xu, Qihang Lin, Tianbao Yang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3821-3830
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Hongteng Xu, Dixin Luo, Hongyuan Zha; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3831-3840
Adaptive Consensus ADMM for Distributed Optimization
Zheng Xu, Gavin Taylor, Hao Li, Mário A. T. Figueiredo, Xiaoming Yuan, Tom Goldstein; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3841-3850
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3851-3860
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3861-3870
On The Projection Operator to A Three-view Cardinality Constrained Set
Haichuan Yang, Shupeng Gui, Chuyang Ke, Daniel Stefankovic, Ryohei Fujimaki, Ji Liu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3871-3880
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov, Taylor Berg-Kirkpatrick; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3881-3890
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang, Denis Krompass, Volker Tresp; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3891-3900
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A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Tianbao Yang, Qihang Lin, Lijun Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3901-3910
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Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang, Aurélie C. Lozano; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3911-3920
Scalable Bayesian Rule Lists
Hongyu Yang, Cynthia Rudin, Margo Seltzer; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3921-3930
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Approximate Newton Methods and Their Local Convergence
Haishan Ye, Luo Luo, Zhihua Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3931-3939
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
Jianbo Ye, James Z. Wang, Jia Li; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3940-3948
Latent Feature Lasso
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3949-3957
Combined Group and Exclusive Sparsity for Deep Neural Networks
Jaehong Yoon, Sung Ju Hwang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3958-3966
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Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data
Manzil Zaheer, Amr Ahmed, Alexander J. Smola; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3967-3976
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Canopy Fast Sampling with Cover Trees
Manzil Zaheer, Satwik Kottur, Amr Ahmed, José Moura, Alex Smola; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3977-3986
Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, Surya Ganguli; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3987-3995
Stochastic Gradient Monomial Gamma Sampler
Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:3996-4005
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Adversarial Feature Matching for Text Generation
Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4006-4015
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Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4016-4025
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Chenzi Zhang, Shuguang Hu, Zhihao Gavin Tang, T-H. Hubert Chan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4026-4034
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ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
Hantian Zhang, Jerry Li, Kaan Kara, Dan Alistarh, Ji Liu, Ce Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4035-4043
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Convexified Convolutional Neural Networks
Yuchen Zhang, Percy Liang, Martin J. Wainwright; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4044-4053
Projection-free Distributed Online Learning in Networks
Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4054-4062
Multi-Class Optimal Margin Distribution Machine
Teng Zhang, Zhi-Hua Zhou; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4063-4071
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Leveraging Node Attributes for Incomplete Relational Data
He Zhao, Lan Du, Wray Buntine; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4072-4081
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Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao, Siyu Liao, Yanzhi Wang, Zhe Li, Jian Tang, Bo Yuan; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4082-4090
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Learning Hierarchical Features from Deep Generative Models
Shengjia Zhao, Jiaming Song, Stefano Ermon; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4091-4099
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi S. Jaakkola, Matt T. Bianchi; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4100-4109
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Follow the Moving Leader in Deep Learning
Shuai Zheng, James T. Kwok; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4110-4119
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhi-Ming Ma, Tie-Yan Liu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4120-4129
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Kai Zheng, Wenlong Mou, Liwei Wang; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4130-4139
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong, Zhao Song, Prateek Jain, Peter L. Bartlett, Inderjit S. Dhillon; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4140-4149
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Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Chaoxu Zhou, Wenbo Gao, Donald Goldfarb; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4150-4159
Identify the Nash Equilibrium in Static Games with Random Payoffs
Yichi Zhou, Jialian Li, Jun Zhu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4160-4169
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications
Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4170-4179
High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm
Rongda Zhu, Lingxiao Wang, Chengxiang Zhai, Quanquan Gu; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4180-4188
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Recurrent Highway Networks
Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnı́k, Jürgen Schmidhuber; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4189-4198
Online Learning to Rank in Stochastic Click Models
Masrour Zoghi, Tomas Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvari, Zheng Wen; Proceedings of the 34th International Conference on Machine Learning, PMLR 70:4199-4208
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