ICLR 2020

687 papers

Disentangling Factors of Variations Using Few Labels

Francesco Locatello, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf

Contrastive Learning of Structured World Models

Thomas Kipf, Elise van der Pol, Max Welling

Functional vs. parametric equivalence of ReLU networks

Mary Phuong, Christoph H. Lampert

Encoding word order in complex embeddings

Benyou Wang, Donghao Zhao, Christina Lioma, Qiuchi Li, Peng Zhang

Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models

Joan Serrà, David Álvarez, Vicenç Gómez, Olga Slizovskaia, José F. Núñez

RTFM: Generalising to New Environment Dynamics via Reading

Victor Zhong, Tim Rocktäschel, Edward Grefenstette

What graph neural networks cannot learn: depth vs width

Andreas Loukas

Progressive Memory Banks for Incremental Domain Adaptation

Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart

Automated curriculum generation through setter-solver interactions

Sébastien Racanière, Andrew Lampinen, Adam Santoro, David Reichert, Vlad Firoiu

On Identifiability in Transformers

Gino Brunner, Yang Liu, Damian Pascual, Oliver Richter, Massimiliano Ciaramita

Exploring Model-based Planning with Policy Networks

Tingwu Wang, Jimmy Ba

Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling

Yuping Luo, Huazhe Xu, Tengyu Ma

Geometric Insights into the Convergence of Nonlinear TD Learning

David Brandfonbrener, Joan Bruna

Few-shot Text Classification with Distributional Signatures

Yujia Bao, Menghua Wu, Shiyu Chang, Regina Barzilay

Escaping Saddle Points Faster with Stochastic Momentum

Jun-Kun Wang, Chi-Heng Lin, Jacob Abernethy

Adversarial Policies: Attacking Deep Reinforcement Learning

Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation

Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine

Neural Network Branching for Neural Network Verification

Jingyue Lu, M. Pawan Kumar

GLAD: Learning Sparse Graph Recovery

Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinivas Aluru

DDSP: Differentiable Digital Signal Processing

Jesse Engel, Lamtharn (Hanoi) Hantrakul, Chenjie Gu, Adam Roberts

Pruned Graph Scattering Transforms

Vassilis N. Ioannidis, Siheng Chen, Georgios B. Giannakis

Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model

Wenhan Xiong, Jingfei Du, William Yang Wang, Veselin Stoyanov

Can gradient clipping mitigate label noise?

Aditya Krishna Menon, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar

Editable Neural Networks

Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Pyrkin, Sergei Popov, Artem Babenko

LEARNING EXECUTION THROUGH NEURAL CODE FUSION

Zhan Shi, Kevin Swersky, Daniel Tarlow, Parthasarathy Ranganathan, Milad Hashemi

FasterSeg: Searching for Faster Real-time Semantic Segmentation

Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li

Difference-Seeking Generative Adversarial Network--Unseen Sample Generation

Yi Lin Sung, Sung-Hsien Hsieh, Soo-Chang Pei, Chun-Shien Lu

Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity

Jingzhao Zhang, Tianxing He, Suvrit Sra, Ali Jadbabaie

Stochastic AUC Maximization with Deep Neural Networks

Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang

Semantically-Guided Representation Learning for Self-Supervised Monocular Depth

Vitor Guizilini, Rui Hou, Jie Li, Rares Ambrus, Adrien Gaidon

MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius

Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong

Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions

Yao Qin, Nicholas Frosst, Sara Sabour, Colin Raffel, Garrison Cottrell

Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information

Yichi Zhou, Jialian Li, Jun Zhu

GAT: Generative Adversarial Training for Adversarial Example Detection and Robust Classification

Xuwang Yin, Soheil Kolouri, Gustavo K Rohde

Variational Recurrent Models for Solving Partially Observable Control Tasks

Dongqi Han, Kenji Doya, Jun Tani

Population-Guided Parallel Policy Search for Reinforcement Learning

Whiyoung Jung, Giseung Park, Youngchul Sung

Compositional languages emerge in a neural iterated learning model

Yi Ren, Shangmin Guo, Matthieu Labeau, Shay B. Cohen, Simon Kirby

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

Hung-Yu Tseng, Hsin-Ying Lee, Jia-Bin Huang, Ming-Hsuan Yang

Black-Box Adversarial Attack with Transferable Model-based Embedding

Zhichao Huang, Tong Zhang

I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively

Haotao Wang, Tianlong Chen, Zhangyang Wang, Kede Ma

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models

Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang

Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP

Yuanhao Wang, Kefan Dong, Xiaoyu Chen, Liwei Wang

Deep Network Classification by Scattering and Homotopy Dictionary Learning

John Zarka, Louis Thiry, Tomás Angles, Stephane Mallat

Data-Independent Neural Pruning via Coresets

Ben Mussay, Margarita Osadchy, Vladimir braverman, Samson Zhou, Dan Feldman

Bounds on Over-Parameterization for Guaranteed Existence of Descent Paths in Shallow ReLU Networks

Arsalan Sharifnassab, Saber Salehkaleybar, S. Jamaloddin Golestani

Novelty Detection Via Blurring

Sungik Choi, Sae-Young Chung

Piecewise linear activations substantially shape the loss surfaces of neural networks

Fengxiang He, Bohan Wang, Dacheng Tao

Relational State-Space Model for Stochastic Multi-Object Systems

Fan Yang, Ling Chen, Fan Zhou, Yusong Gao, Wei Cao

Learning Efficient Parameter Server Synchronization Policies for Distributed SGD

Rong Zhu, Sheng Yang, Andreas Pfadler, Zhengping Qian, Jingren Zhou

Action Semantics Network: Considering the Effects of Actions in Multiagent Systems

Weixun Wang, Tianpei Yang, Yong Liu, Jianye Hao, Xiaotian Hao

Vid2Game: Controllable Characters Extracted from Real-World Videos

Oran Gafni, Lior Wolf, Yaniv Taigman

Self-Adversarial Learning with Comparative Discrimination for Text Generation

Wangchunshu Zhou, Tao Ge, Ke Xu, Furu Wei, Ming Zhou

Robust training with ensemble consensus

Jisoo Lee, Sae-Young Chung

Identifying through Flows for Recovering Latent Representations

Shen Li, Bryan Hooi, Gim Hee Lee

Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing

Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong

Optimistic Exploration even with a Pessimistic Initialisation

Tabish Rashid, Bei Peng, Wendelin Boehmer, Shimon Whiteson

VL-BERT: Pre-training of Generic Visual-Linguistic Representations

Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu

Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation

Hang Gao, Xizhou Zhu, Stephen Lin, Jifeng Dai

Ensemble Distribution Distillation

Andrey Malinin, Bruno Mlodozeniec, Mark Gales

Gap-Aware Mitigation of Gradient Staleness

Saar Barkai, Ido Hakimi, Assaf Schuster

Counterfactuals uncover the modular structure of deep generative models

Michel Besserve, Arash Mehrjou, Remy Sun, Bernhard Schölkopf

Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video

Miguel Jaques, Michael Burke, Timothy Hospedales

Mogrifier LSTM

Gábor Melis, Tomas Kocisky, Phil Blunsom

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality

Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba

A Constructive Prediction of the Generalization Error Across Scales

Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, Nir Shavit

Ridge Regression: Structure, Cross-Validation, and Sketching

Sifan Liu, Edgar Dobriban

Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base

William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler

CLN2INV: Learning Loop Invariants with Continuous Logic Networks

Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gu, Suman Jana

NAS evaluation is frustratingly hard

Antoine Yang, Pedro M. Esperança, Fabio M. Carlucci

Efficient and Information-Preserving Future Frame Prediction and Beyond

Wei Yu, Yichao Lu, Steve Easterbrook, Sanja Fidler

Order Learning and Its Application to Age Estimation

Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee, Chang-Su Kim

Finite Depth and Width Corrections to the Neural Tangent Kernel

Boris Hanin, Mihai Nica

ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

Weihao Yu, Zihang Jiang, Yanfei Dong, Jiashi Feng

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures

Michael S. Ryoo, AJ Piergiovanni, Mingxing Tan, Anelia Angelova

Adversarially Robust Representations with Smooth Encoders

Taylan Cemgil, Sumedh Ghaisas, Krishnamurthy (Dj) Dvijotham, Pushmeet Kohli

From Variational to Deterministic Autoencoders

Partha Ghosh, Mehdi S. M. Sajjadi, Antonio Vergari, Michael Black, Bernhard Schölkopf

Meta-Learning without Memorization

Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn

Computation Reallocation for Object Detection

Feng Liang, CHEN LIN, Ronghao Guo, Ming Sun, Wei Wu

Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents

Christian Rupprecht, Cyril Ibrahim, Christopher J. Pal

A Fair Comparison of Graph Neural Networks for Graph Classification

Federico Errica, Marco Podda, Davide Bacciu, Alessio Micheli

Generalization bounds for deep convolutional neural networks

Philip M. Long, Hanie Sedghi

SAdam: A Variant of Adam for Strongly Convex Functions

Guanghui Wang, Shiyin Lu, Quan Cheng, Wei-Wei Tu, Lijun Zhang

Continual Learning with Bayesian Neural Networks for Non-Stationary Data

Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt, Stephan Günnemann

Multiplicative Interactions and Where to Find Them

Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick, Jonathan Schwarz, Jack Rae

Influence-Based Multi-Agent Exploration

Tonghan Wang*, Jianhao Wang*, Yi Wu, Chongjie Zhang

FEW-SHOT LEARNING ON GRAPHS VIA SUPER-CLASSES BASED ON GRAPH SPECTRAL MEASURES

Jatin Chauhan, Deepak Nathani, Manohar Kaul

On Computation and Generalization of Generative Adversarial Imitation Learning

Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li

A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning

Shahbaz Rezaei, Xin Liu

Low-Resource Knowledge-Grounded Dialogue Generation

Xueliang Zhao, Wei Wu, Chongyang Tao, Can Xu, Dongyan Zhao

Deep 3D Pan via local adaptive "t-shaped" convolutions with global and local adaptive dilations

Juan Luis Gonzalez Bello, Munchurl Kim

Tree-Structured Attention with Hierarchical Accumulation

Xuan-Phi Nguyen, Shafiq Joty, Steven Hoi, Richard Socher

The asymptotic spectrum of the Hessian of DNN throughout training

Arthur Jacot, Franck Gabriel, Clement Hongler

Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games

Zuyue Fu, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

In Search for a SAT-friendly Binarized Neural Network Architecture

Nina Narodytska, Hongce Zhang, Aarti Gupta, Toby Walsh

Generative Ratio Matching Networks

Akash Srivastava, Kai Xu, Michael U. Gutmann, Charles Sutton

Learning to Represent Programs with Property Signatures

Augustus Odena, Charles Sutton

V4D: 4D Convolutional Neural Networks for Video-level Representation Learning

Shiwen Zhang, Sheng Guo, Weilin Huang, Matthew R. Scott, Limin Wang

HOPPITY: LEARNING GRAPH TRANSFORMATIONS TO DETECT AND FIX BUGS IN PROGRAMS

Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song

Option Discovery using Deep Skill Chaining

Akhil Bagaria, George Konidaris

Sliced Cramer Synaptic Consolidation for Preserving Deeply Learned Representations

Soheil Kolouri, Nicholas A. Ketz, Andrea Soltoggio, Praveen K. Pilly