ICLR 2020

687 papers

Quantifying the Cost of Reliable Photo Authentication via High-Performance Learned Lossy Representations

Pawel Korus, Nasir Memon

On the Variance of the Adaptive Learning Rate and Beyond

Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu

Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery

Kristian Hartikainen, XINYANG GENG, Tuomas Haarnoja, Sergey Levine

A Theoretical Analysis of the Number of Shots in Few-Shot Learning

Tianshi Cao, Marc T Law, Sanja Fidler

How much Position Information Do Convolutional Neural Networks Encode?

Md Amirul Islam*, Sen Jia*, Neil D. B. Bruce

Unsupervised Model Selection for Variational Disentangled Representation Learning

Sunny Duan, Loic Matthey, Andre Saraiva, Nick Watters, Chris Burgess

Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection

Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou

Hamiltonian Generative Networks

Peter Toth, Danilo J. Rezende, Andrew Jaegle, Sébastien Racanière, Aleksandar Botev

Understanding the Limitations of Variational Mutual Information Estimators

Jiaming Song, Stefano Ermon

CoPhy: Counterfactual Learning of Physical Dynamics

Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, Christian Wolf

GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

Martin Engelcke, Adam R. Kosiorek, Oiwi Parker Jones, Ingmar Posner

Language GANs Falling Short

Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau

Stochastic Conditional Generative Networks with Basis Decomposition

Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu

Estimating counterfactual treatment outcomes over time through adversarially balanced representations

Ioana Bica, Ahmed M Alaa, James Jordon, Mihaela van der Schaar

LEARNED STEP SIZE QUANTIZATION

Steven K. Esser, Jeffrey L. McKinstry, Deepika Bablani, Rathinakumar Appuswamy, Dharmendra S. Modha

On the "steerability" of generative adversarial networks

Ali Jahanian*, Lucy Chai*, Phillip Isola

Gradientless Descent: High-Dimensional Zeroth-Order Optimization

Daniel Golovin, John Karro, Greg Kochanski, Chansoo Lee, Xingyou Song

Reinforced active learning for image segmentation

Arantxa Casanova, Pedro O. Pinheiro, Negar Rostamzadeh, Christopher J. Pal

Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech

David Harwath*, Wei-Ning Hsu*, James Glass

Sign Bits Are All You Need for Black-Box Attacks

Abdullah Al-Dujaili, Una-May O'Reilly

Mirror-Generative Neural Machine Translation

Zaixiang Zheng, Hao Zhou, Shujian Huang, Lei Li, Xin-yu Dai

Deep Semi-Supervised Anomaly Detection

Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints

Mengtian Li, Ersin Yumer, Deva Ramanan

Minimizing FLOPs to Learn Efficient Sparse Representations

Biswajit Paria, Chih-Kuan Yeh, Ian E.H. Yen, Ning Xu, Pradeep Ravikumar

Reanalysis of Variance Reduced Temporal Difference Learning

Tengyu Xu, Zhe Wang, Yi Zhou, Yingbin Liang

Imitation Learning via Off-Policy Distribution Matching

Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

Aniruddh Raghu, Maithra Raghu, Samy Bengio, Oriol Vinyals

Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space

AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alan Aspuru-Guzik

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson

Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin

Colin Wei, Tengyu Ma

Identity Crisis: Memorization and Generalization Under Extreme Overparameterization

Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer

Conditional Learning of Fair Representations

Han Zhao, Amanda Coston, Tameem Adel, Geoffrey J. Gordon

ReMixMatch: Semi-Supervised Learning with Distribution Matching and Augmentation Anchoring

David Berthelot, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Kihyuk Sohn

Inductive Matrix Completion Based on Graph Neural Networks

Muhan Zhang, Yixin Chen

Adaptive Structural Fingerprints for Graph Attention Networks

Kai Zhang, Yaokang Zhu, Jun Wang, Jie Zhang

Your classifier is secretly an energy based model and you should treat it like one

Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen, David Duvenaud, Mohammad Norouzi

CAQL: Continuous Action Q-Learning

Moonkyung Ryu, Yinlam Chow, Ross Anderson, Christian Tjandraatmadja, Craig Boutilier

Duration-of-Stay Storage Assignment under Uncertainty

Michael Lingzhi Li, Elliott Wolf, Daniel Wintz

Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks

Christopher J. Cueva, Peter Y. Wang, Matthew Chin, Xue-xin Wei

Deep neuroethology of a virtual rodent

Josh Merel, Diego Aldarondo, Jesse Marshall, Yuval Tassa, Greg Wayne

Learning Heuristics for Quantified Boolean Formulas through Reinforcement Learning

Gil Lederman, Markus Rabe, Sanjit Seshia, Edward A. Lee

Pure and Spurious Critical Points: a Geometric Study of Linear Networks

Matthew Trager, Kathlén Kohn, Joan Bruna

Neural Text Generation With Unlikelihood Training

Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho

Semi-Supervised Generative Modeling for Controllable Speech Synthesis

Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, RJ Skerry-Ryan

Dynamic Time Lag Regression: Predicting What & When

Mandar Chandorkar, Cyril Furtlehner, Bala Poduval, Enrico Camporeale, Michele Sebag

Scalable Model Compression by Entropy Penalized Reparameterization

Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava

AMRL: Aggregated Memory For Reinforcement Learning

Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang

Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform

Jun Li, Fuxin Li, Sinisa Todorovic

Unpaired Point Cloud Completion on Real Scans using Adversarial Training

Xuelin Chen, Baoquan Chen, Niloy J. Mitra

Dynamics-Aware Unsupervised Discovery of Skills

Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman

Adjustable Real-time Style Transfer

Mohammad Babaeizadeh, Golnaz Ghiasi

Stochastic Weight Averaging in Parallel: Large-Batch Training That Generalizes Well

Vipul Gupta, Santiago Akle Serrano, Dennis DeCoste

Short and Sparse Deconvolution --- A Geometric Approach

Yenson Lau, Qing Qu, Han-wen Kuo, Pengcheng Zhou, Yuqian Zhang

Selection via Proxy: Efficient Data Selection for Deep Learning

Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis

Global Relational Models of Source Code

Vincent J. Hellendoorn, Charles Sutton, Rishabh Singh, Petros Maniatis, David Bieber

Detecting Extrapolation with Local Ensembles

David Madras, James Atwood, Alexander D'Amour

Learning to Link

Maria-Florina Balcan, Travis Dick, Manuel Lang

Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation

Ziyang Tang*, Yihao Feng*, Lihong Li, Dengyong Zhou, Qiang Liu

Adversarially robust transfer learning

Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer

Optimal Strategies Against Generative Attacks

Roy Mor, Erez Peterfreund, Matan Gavish, Amir Globerson

Overlearning Reveals Sensitive Attributes

Congzheng Song, Vitaly Shmatikov

Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness

Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin

Learning Compositional Koopman Operators for Model-Based Control

Yunzhu Li, Hao He, Jiajun Wu, Dina Katabi, Antonio Torralba

CLEVRER: Collision Events for Video Representation and Reasoning

Kexin Yi*, Chuang Gan*, Yunzhu Li, Pushmeet Kohli, Jiajun Wu

Differentially Private Meta-Learning

Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar

One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation

Shunshi Zhang, Bradly C. Stadie

Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples

Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci

Are Transformers universal approximators of sequence-to-sequence functions?

Chulhee Yun, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank Reddi, Sanjiv Kumar

Pre-training Tasks for Embedding-based Large-scale Retrieval

Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar

The Logical Expressiveness of Graph Neural Networks

Pablo Barceló, Egor V. Kostylev, Mikaël Monet, Jorge Pérez, Juan Reutter

Deep Imitative Models for Flexible Inference, Planning, and Control

Nicholas Rhinehart, Rowan McAllister, Sergey Levine

CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning

Jiachen Yang, Alireza Nakhaei, David Isele, Kikuo Fujimura, Hongyuan Zha

Robust And Interpretable Blind Image Denoising Via Bias-Free Convolutional Neural Networks

Sreyas Mohan, Zahra Kadkhodaie, Eero P. Simoncelli, Carlos Fernandez-Granda

Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets

Mingrui Liu, Youssef Mroueh, Jerret Ross, Wei Zhang, Xiaodong Cui

The Break-Even Point on Optimization Trajectories of Deep Neural Networks

Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor

DeepV2D: Video to Depth with Differentiable Structure from Motion

Zachary Teed, Jia Deng

Learning Space Partitions for Nearest Neighbor Search

Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP

Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack

Minhao Cheng, Simranjit Singh, Patrick H. Chen, Pin-Yu Chen, Sijia Liu

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma

RaCT: Toward Amortized Ranking-Critical Training For Collaborative Filtering

Sam Lobel*, Chunyuan Li*, Jianfeng Gao, Lawrence Carin

Intrinsic Motivation for Encouraging Synergistic Behavior

Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, Abhinav Gupta

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation

Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh

Disentangling neural mechanisms for perceptual grouping

Junkyung Kim*, Drew Linsley*, Kalpit Thakkar, Thomas Serre

Recurrent neural circuits for contour detection

Drew Linsley*, Junkyung Kim*, Alekh Ashok, Thomas Serre

Locality and Compositionality in Zero-Shot Learning

Tristan Sylvain, Linda Petrini, Devon Hjelm

Understanding Knowledge Distillation in Non-autoregressive Machine Translation

Chunting Zhou, Jiatao Gu, Graham Neubig

Thieves on Sesame Street! Model Extraction of BERT-based APIs

Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, Mohit Iyyer

Fast is better than free: Revisiting adversarial training

Eric Wong, Leslie Rice, J. Zico Kolter

DBA: Distributed Backdoor Attacks against Federated Learning

Chulin Xie, Keli Huang, Pin-Yu Chen, Bo Li

DeFINE: Deep Factorized Input Token Embeddings for Neural Sequence Modeling

Sachin Mehta, Rik Koncel-Kedziorski, Mohammad Rastegari, Hannaneh Hajishirzi

Sampling-Free Learning of Bayesian Quantized Neural Networks

Jiahao Su, Milan Cvitkovic, Furong Huang

Learning to solve the credit assignment problem

Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording

Four Things Everyone Should Know to Improve Batch Normalization

Cecilia Summers, Michael J. Dinneen

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving

Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss

SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum

Jianyu Wang, Vinayak Tantia, Nicolas Ballas, Michael Rabbat

MetaPix: Few-Shot Video Retargeting

Jessica Lee, Deva Ramanan, Rohit Girdhar

Learning to Learn by Zeroth-Order Oracle

Yangjun Ruan, Yuanhao Xiong, Sashank Reddi, Sanjiv Kumar, Cho-jui Hsieh

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

Erik Wijmans, Abhishek Kadian, Ari Morcos, Stefan Lee, Irfan Essa

PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction

Sangdon Park, Osbert Bastani, Nikolai Matni, Insup Lee