ICLR 2020

687 papers

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar

Program Guided Agent

Shao-Hua Sun, Te-Lin Wu, Joseph J. Lim

SELF: Learning to Filter Noisy Labels with Self-Ensembling

Duc Tam Nguyen, Chaithanya Kumar Mummadi, Thi Phuong Nhung Ngo, Thi Hoai Phuong Nguyen, Laura Beggel

Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation

Yu Chen, Lingfei Wu, Mohammed J. Zaki

Sharing Knowledge in Multi-Task Deep Reinforcement Learning

Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

On the Weaknesses of Reinforcement Learning for Neural Machine Translation

Leshem Choshen, Lior Fox, Zohar Aizenbud, Omri Abend

StructPool: Structured Graph Pooling via Conditional Random Fields

Hao Yuan, Shuiwang Ji

Learning deep graph matching with channel-independent embedding and Hungarian attention

Tianshu Yu, Runzhong Wang, Junchi Yan, baoxin Li

Sparse Coding with Gated Learned ISTA

Kailun Wu, Yiwen Guo, Ziang Li, Changshui Zhang

Graph inference learning for semi-supervised classification

Chunyan Xu, Zhen Cui, Xiaobin Hong, Tong Zhang, Jian Yang

Graph Neural Networks Exponentially Lose Expressive Power for Node Classification

Kenta Oono, Taiji Suzuki

SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Siddharth Reddy, Anca D. Dragan, Sergey Levine

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Sergei Popov, Stanislav Morozov, Artem Babenko

Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

Gengchen Mai, Krzysztof Janowicz, Bo Yan, Rui Zhu, Ling Cai

Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification

Yixiao Ge, Dapeng Chen, hongsheng Li

Automatically Discovering and Learning New Visual Categories with Ranking Statistics

Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Ehrhardt, Andrea Vedaldi, Andrew Zisserman

Maxmin Q-learning: Controlling the Estimation Bias of Q-learning

Qingfeng Lan, Yangchen Pan, Alona Fyshe, Martha White

CATER: A diagnostic dataset for Compositional Actions & TEmporal Reasoning

Rohit Girdhar, Deva Ramanan

Federated Adversarial Domain Adaptation

Xingchao Peng, Zijun Huang, Yizhe Zhu, Kate Saenko

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

Fan-Yun Sun, Jordan Hoffman, Vikas Verma, Jian Tang

Depth-Adaptive Transformer

Maha Elbayad, Jiatao Gu, Edouard Grave, Michael Auli

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures

Huanrui Yang, Wei Wen, Hai Li

BackPACK: Packing more into Backprop

Felix Dangel, Frederik Kunstner, Philipp Hennig

On Robustness of Neural Ordinary Differential Equations

Hanshu Yan, JIAWEI DU, Vincent Tan, Jiashi Feng

Evaluating The Search Phase of Neural Architecture Search

Kaicheng Yu, Christian Sciuto, Martin Jaggi, Claudiu Musat, Mathieu Salzmann

Diverse Trajectory Forecasting with Determinantal Point Processes

Ye Yuan, Kris M. Kitani

ProxSGD: Training Structured Neural Networks under Regularization and Constraints

Yang Yang, Yaxiong Yuan, Avraam Chatzimichailidis, Ruud JG van Sloun, Lei Lei

GenDICE: Generalized Offline Estimation of Stationary Values

Ruiyi Zhang*, Bo Dai*, Lihong Li, Dale Schuurmans

LAMOL: LAnguage MOdeling for Lifelong Language Learning

Fan-Keng Sun*, Cheng-Hao Ho*, Hung-yi Lee

Learning Expensive Coordination: An Event-Based Deep RL Approach

Zhenyu Shi*, Runsheng Yu*, Xinrun Wang*, Rundong Wang, Youzhi Zhang

Curvature Graph Network

Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen

Distance-Based Learning from Errors for Confidence Calibration

Chen Xing, Sercan Arik, Zizhao Zhang, Tomas Pfister

Deep Learning of Determinantal Point Processes via Proper Spectral Sub-gradient

Tianshu Yu, Yikang LI, baoxin Li

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio

Defending Against Physically Realizable Attacks on Image Classification

Tong Wu, Liang Tong, Yevgeniy Vorobeychik

Automated Relational Meta-learning

Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding

To Relieve Your Headache of Training an MRF, Take AdVIL

Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu

Estimating Gradients for Discrete Random Variables by Sampling without Replacement

Wouter Kool, Herke van Hoof, Max Welling

Linear Symmetric Quantization of Neural Networks for Low-precision Integer Hardware

Xiandong Zhao, Ying Wang, Xuyi Cai, Cheng Liu, Lei Zhang

Learning to Control PDEs with Differentiable Physics

Philipp Holl, Nils Thuerey, Vladlen Koltun

Weakly Supervised Clustering by Exploiting Unique Class Count

Mustafa Umit Oner, Hwee Kuan Lee, Wing-Kin Sung

Scalable and Order-robust Continual Learning with Additive Parameter Decomposition

Jaehong Yoon, Saehoon Kim, Eunho Yang, Sung Ju Hwang

Intensity-Free Learning of Temporal Point Processes

Oleksandr Shchur, Marin Biloš, Stephan Günnemann

Continual Learning with Adaptive Weights (CLAW)

Tameem Adel, Han Zhao, Richard E. Turner

A Signal Propagation Perspective for Pruning Neural Networks at Initialization

Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr

Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets

Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma

Transferable Perturbations of Deep Feature Distributions

Nathan Inkawhich, Kevin Liang, Lawrence Carin, Yiran Chen

A Learning-based Iterative Method for Solving Vehicle Routing Problems

Hao Lu, Xingwen Zhang, Shuang Yang

Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, Jason Weston

White Noise Analysis of Neural Networks

Ali Borji, Sikun Lin

AutoQ: Automated Kernel-Wise Neural Network Quantization

Qian Lou, Feng Guo, Minje Kim, Lantao Liu, Lei Jiang.

Understanding Architectures Learnt by Cell-based Neural Architecture Search

YAO SHU, Wei Wang, Shaofeng Cai

Neural Machine Translation with Universal Visual Representation

Zhuosheng Zhang, Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita

SVQN: Sequential Variational Soft Q-Learning Networks

Shiyu Huang, Hang Su, Jun Zhu, Ting Chen

Ranking Policy Gradient

Kaixiang Lin, Jiayu Zhou

Tranquil Clouds: Neural Networks for Learning Temporally Coherent Features in Point Clouds

Lukas Prantl, Nuttapong Chentanez, Stefan Jeschke, Nils Thuerey

On Mutual Information Maximization for Representation Learning

Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic

Observational Overfitting in Reinforcement Learning

Xingyou Song, YiDing Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur

Enhancing Transformation-Based Defenses Against Adversarial Attacks with a Distribution Classifier

Connie Kou, Hwee Kuan Lee, Ee-Chien Chang, Teck Khim Ng

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Yuhang Li, Xin Dong, Wei Wang

Principled Weight Initialization for Hypernetworks

Oscar Chang, Lampros Flokas, Hod Lipson

Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information

Yichi Zhou, Tongzheng Ren, Jialian Li, Dong Yan, Jun Zhu

Knowledge Consistency between Neural Networks and Beyond

Ruofan Liang, Tianlin Li, Longfei Li, Jing Wang, Quanshi Zhang

PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search

Yuhui Xu, Lingxi Xie, XIAOPENG ZHANG, Xin Chen, Guo-Jun Qi

Image-guided Neural Object Rendering

Justus Thies, Michael Zollhöfer, Christian Theobalt, Marc Stamminger, Matthias Nießner

Implicit Bias of Gradient Descent based Adversarial Training on Separable Data

Yan Li, Ethan X.Fang, Huan Xu, Tuo Zhao

TabFact: A Large-scale Dataset for Table-based Fact Verification

Wenhu Chen, Hongmin Wang, Jianshu Chen, Yunkai Zhang, Hong Wang

ES-MAML: Simple Hessian-Free Meta Learning

Xingyou Song, Wenbo Gao, Yuxiang Yang, Krzysztof Choromanski, Aldo Pacchiano

Neural Stored-program Memory

Hung Le, Truyen Tran, Svetha Venkatesh

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation

Suraj Nair, Chelsea Finn

Multi-agent Reinforcement Learning for Networked System Control

Tianshu Chu, Sandeep Chinchali, Sachin Katti

On the Convergence of FedAvg on Non-IID Data

Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang

FSPool: Learning Set Representations with Featurewise Sort Pooling

Yan Zhang, Jonathon Hare, Adam Prugel-Bennett

Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction

Taeuk Kim, Jihun Choi, Daniel Edmiston, Sang-goo Lee

Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning

Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun

Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks

Tianyu Pang*, Kun Xu*, Jun Zhu

Theory and Evaluation Metrics for Learning Disentangled Representations

Kien Do, Truyen Tran

Measuring Compositional Generalization: A Comprehensive Method on Realistic Data

Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness

Tianyu Pang, Kun Xu, Yinpeng Dong, Chao Du, Ning Chen

The Implicit Bias of Depth: How Incremental Learning Drives Generalization

Daniel Gissin, Shai Shalev-shwartz, Amit Daniely

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

Learning the Arrow of Time for Problems in Reinforcement Learning

Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives

Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine

Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach

Kimon Antonakopoulos, E. Veronica Belmega, Panayotis Mertikopoulos

Robust Local Features for Improving the Generalization of Adversarial Training

Chuanbiao Song, Kun He, Jiadong Lin, Liwei Wang, John E. Hopcroft

Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification

Bennet Breier, Arno Onken

Learning Disentangled Representations for CounterFactual Regression

Negar Hassanpour, Russell Greiner

Exploration in Reinforcement Learning with Deep Covering Options

Yuu Jinnai, Jee Won Park, Marlos C. Machado, George Konidaris

Enhancing Adversarial Defense by k-Winners-Take-All

Chang Xiao, Peilin Zhong, Changxi Zheng

AE-OT: A NEW GENERATIVE MODEL BASED ON EXTENDED SEMI-DISCRETE OPTIMAL TRANSPORT

Dongsheng An, Yang Guo, Na Lei, Zhongxuan Luo, Shing-Tung Yau

Logic and the 2-Simplicial Transformer

James Clift, Dmitry Doryn, Daniel Murfet, James Wallbridge

Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards

Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari

Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking

Yunhan Jia, Yantao Lu, Junjie Shen, Qi Alfred Chen, Hao Chen

Data-dependent Gaussian Prior Objective for Language Generation

Zuchao Li, Rui Wang, Kehai Chen, Masso Utiyama, Eiichiro Sumita

DivideMix: Learning with Noisy Labels as Semi-supervised Learning

Junnan Li, Richard Socher, Steven C.H. Hoi

Improving Adversarial Robustness Requires Revisiting Misclassified Examples

Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer

Interpretable Complex-Valued Neural Networks for Privacy Protection

Liyao Xiang, Hao Zhang, Haotian Ma, Yifan Zhang, Jie Ren

Accelerating SGD with momentum for over-parameterized learning

Chaoyue Liu, Mikhail Belkin

A critical analysis of self-supervision, or what we can learn from a single image

Asano YM., Rupprecht C., Vedaldi A.