ICLR 2021

859 papers

Contemplating Real-World Object Classification

Ali Borji

Counterfactual Generative Networks

Axel Sauer, Andreas Geiger

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation

Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian

Active Contrastive Learning of Audio-Visual Video Representations

Shuang Ma, Zhaoyang Zeng, Daniel McDuff, Yale Song

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang

Better Fine-Tuning by Reducing Representational Collapse

Armen Aghajanyan, Akshat Shrivastava, Anchit Gupta, Naman Goyal, Luke Zettlemoyer

Perceptual Adversarial Robustness: Defense Against Unseen Threat Models

Cassidy Laidlaw, Sahil Singla, Soheil Feizi

A Unified Approach to Interpreting and Boosting Adversarial Transferability

Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang

Learning Subgoal Representations with Slow Dynamics

Siyuan Li, Lulu Zheng, Jianhao Wang, Chongjie Zhang

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights

Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

Xiaoxiao Li, Meirui Jiang, Xiaofei Zhang, Michael Kamp, Qi Dou

Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits

Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li

Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis

Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal

Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs

Jonathan Frankle, David J. Schwab, Ari S. Morcos

Fourier Neural Operator for Parametric Partial Differential Equations

Zongyi Li, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya

Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation

Peiye Zhuang, Oluwasanmi O Koyejo, Alex Schwing

GraphCodeBERT: Pre-training Code Representations with Data Flow

Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang

MoPro: Webly Supervised Learning with Momentum Prototypes

Junnan Li, Caiming Xiong, Steven Hoi

Isotropy in the Contextual Embedding Space: Clusters and Manifolds

Xingyu Cai, Jiaji Huang, Yuchen Bian, Kenneth Church

On Learning Universal Representations Across Languages

Xiangpeng Wei, Rongxiang Weng, Yue Hu, Luxi Xing, Heng Yu

Towards Impartial Multi-task Learning

Liyang Liu, Yi Li, Zhanghui Kuang, Jing-Hao Xue, Yimin Chen

Isometric Propagation Network for Generalized Zero-shot Learning

LU LIU, Tianyi Zhou, Guodong Long, Jing Jiang, Xuanyi Dong

A Universal Representation Transformer Layer for Few-Shot Image Classification

LU LIU, William L. Hamilton, Guodong Long, Jing Jiang, Hugo Larochelle

Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters & Less Data

Jonathan Pilault, Amine El hattami, Christopher Pal

One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks

Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan

Self-supervised Representation Learning with Relative Predictive Coding

Yao-Hung Hubert Tsai, Martin Q. Ma, Muqiao Yang, Han Zhao, Louis-Philippe Morency

Creative Sketch Generation

Songwei Ge, Vedanuj Goswami, Larry Zitnick, Devi Parikh

Impact of Representation Learning in Linear Bandits

Jiaqi Yang, Wei Hu, Jason D. Lee, Simon Shaolei Du

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets

Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang

Effective and Efficient Vote Attack on Capsule Networks

Jindong Gu, Baoyuan Wu, Volker Tresp

FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization

Lanqing Li, Rui Yang, Dijun Luo

Graph Edit Networks

Benjamin Paassen, Daniele Grattarola, Daniele Zambon, Cesare Alippi, Barbara Hammer

Taking Notes on the Fly Helps Language Pre-Training

Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He

Efficient Certified Defenses Against Patch Attacks on Image Classifiers

Jan Hendrik Metzen, Maksym Yatsura

Distilling Knowledge from Reader to Retriever for Question Answering

Gautier Izacard, Edouard Grave

Modelling Hierarchical Structure between Dialogue Policy and Natural Language Generator with Option Framework for Task-oriented Dialogue System

Jianhong Wang, yuan zhang, Tae-kyun Kim, Yunjie Gu

Model-Based Offline Planning

Arthur Argenson, Gabriel Dulac-Arnold

On the Dynamics of Training Attention Models

Haoye Lu, Yongyi Mao, Amiya Nayak

CPR: Classifier-Projection Regularization for Continual Learning

Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, Taesup Moon

GAN2GAN: Generative Noise Learning for Blind Denoising with Single Noisy Images

Sungmin Cha, Taeeon Park, Byeongjoon Kim, Jongduk Baek, Taesup Moon

Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces

Yatin Nandwani, Deepanshu Jindal, Mausam ., Parag Singla

On the Universality of Rotation Equivariant Point Cloud Networks

Nadav Dym, Haggai Maron

Efficient Continual Learning with Modular Networks and Task-Driven Priors

Tom Véniat, Ludovic DENOYER, MarcAurelio Ranzato

Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Shikuang Deng, Shi Gu

Contrastive Learning with Adversarial Perturbations for Conditional Text Generation

Seanie Lee, Dong Bok Lee, Sung Ju Hwang

Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning

Wonyong Jeong, Jaehong Yoon, Eunho Yang, Sung Ju Hwang

Accurate Learning of Graph Representations with Graph Multiset Pooling

Jinheon Baek, Minki Kang, Sung Ju Hwang

Removing Undesirable Feature Contributions Using Out-of-Distribution Data

Saehyung Lee, Changhwa Park, HyunGyu Lee, Jihun Yi, Jonghyun Lee

DINO: A Conditional Energy-Based GAN for Domain Translation

Konstantinos Vougioukas, Stavros Petridis, Maja Pantic

Rapid Task-Solving in Novel Environments

Samuel Ritter, Ryan Faulkner, Laurent Sartran, Adam Santoro, Matthew Botvinick

Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition

Seon-Ho Lee, Chang-Su Kim

On the Universality of the Double Descent Peak in Ridgeless Regression

David Holzmüller

Graph Coarsening with Neural Networks

Chen Cai, Dingkang Wang, Yusu Wang

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods

Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon

Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study

Zhiqiang Shen, Zechun Liu, Dejia Xu, Zitian Chen, Kwang-Ting Cheng

Learning Task-General Representations with Generative Neuro-Symbolic Modeling

Reuben Feinman, Brenden M. Lake

Average-case Acceleration for Bilinear Games and Normal Matrices

Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur

Representation Learning for Sequence Data with Deep Autoencoding Predictive Components

Junwen Bai, Weiran Wang, Yingbo Zhou, Caiming Xiong

Sharper Generalization Bounds for Learning with Gradient-dominated Objective Functions

Yunwen Lei, Yiming Ying

Hierarchical Reinforcement Learning by Discovering Intrinsic Options

Jesse Zhang, Haonan Yu, Wei Xu

Mixed-Features Vectors and Subspace Splitting

Alejandro Pimentel-Alarcón, Daniel L. Pimentel-Alarcón

Neural Pruning via Growing Regularization

Huan Wang, Can Qin, Yulun Zhang, Yun Fu

On Position Embeddings in BERT

Benyou Wang, Lifeng Shang, Christina Lioma, Xin Jiang, Hao Yang

Effective Abstract Reasoning with Dual-Contrast Network

Tao Zhuo, Mohan Kankanhalli

Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation

Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, Noah Smith

IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning

Manli Zhang, Jianhong Zhang, Zhiwu Lu, Tao Xiang, Mingyu Ding

Trusted Multi-View Classification

Zongbo Han, Changqing Zhang, Huazhu Fu, Joey Tianyi Zhou

A Discriminative Gaussian Mixture Model with Sparsity

Hideaki Hayashi, Seiichi Uchida

Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning

Kanil Patel, William H. Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang

Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization

Judy Borowski, Roland Simon Zimmermann, Judith Schepers, Robert Geirhos, Thomas S. A. Wallis

VTNet: Visual Transformer Network for Object Goal Navigation

Heming Du, Xin Yu, Liang Zheng

Interpreting and Boosting Dropout from a Game-Theoretic View

Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie

Training with Quantization Noise for Extreme Model Compression

Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Remi Gribonval

Learning with AMIGo: Adversarially Motivated Intrinsic Goals

Andres Campero, Roberta Raileanu, Heinrich Küttler, Joshua B. Tenenbaum, Tim Rocktäschel

Conformation-Guided Molecular Representation with Hamiltonian Neural Networks

Ziyao Li, Shuwen Yang, Guojie Song, Lingsheng Cai

Bayesian Context Aggregation for Neural Processes

Michael Volpp, Fabian Flürenbrock, Lukas Grossberger, Christian Daniel, Gerhard Neumann

Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs

Zhen Han, Peng Chen, Yunpu Ma, Volker Tresp

Tilted Empirical Risk Minimization

Tian Li, Ahmad Beirami, Maziar Sanjabi, Virginia Smith

Text Generation by Learning from Demonstrations

Richard Yuanzhe Pang, He He

Open Question Answering over Tables and Text

Wenhu Chen, Ming-Wei Chang, Eva Schlinger, William Yang Wang, William W. Cohen

Adaptive Universal Generalized PageRank Graph Neural Network

Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry

Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang

Neural Spatio-Temporal Point Processes

Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

Learning Neural Event Functions for Ordinary Differential Equations

Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

Universal approximation power of deep residual neural networks via nonlinear control theory

Paulo Tabuada, Bahman Gharesifard

Learning Manifold Patch-Based Representations of Man-Made Shapes

Dmitriy Smirnov, Mikhail Bessmeltsev, Justin Solomon

SAFENet: A Secure, Accurate and Fast Neural Network Inference

Qian Lou, Yilin Shen, Hongxia Jin, Lei Jiang

High-Capacity Expert Binary Networks

Adrian Bulat, Brais Martinez, Georgios Tzimiropoulos

Wasserstein Embedding for Graph Learning

Soheil Kolouri, Navid Naderializadeh, Gustavo K. Rohde, Heiko Hoffmann

Partitioned Learned Bloom Filters

Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska

MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning

Nanyi Fei, Zhiwu Lu, Tao Xiang, Songfang Huang

Unbiased Teacher for Semi-Supervised Object Detection

Yen-Cheng Liu, CHIH-YAO MA, Zijian He, Chia-Wen Kuo, Kan Chen

Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL

Xiaoyu Chen, Jiachen Hu, Lihong Li, Liwei Wang

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning

Honglu Zhou, Asim Kadav, Farley Lai, Alexandru Niculescu-mizil, Martin Renqiang Min

Large Batch Simulation for Deep Reinforcement Learning

Brennan Shacklett, Erik Wijmans, Aleksei Petrenko, Manolis Savva, Dhruv Batra

Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity

Shaocong Ma, Ziyi Chen, Yi Zhou, Shaofeng Zou

Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization

Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville

Learning Accurate Entropy Model with Global Reference for Image Compression

Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li

Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural Networks by Pruning A Randomly Weighted Network

James Diffenderfer, Bhavya Kailkhura

Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling

Yang Zhao, Jianwen Xie, Ping Li