ICLR 2023

1,573 papers

Fundamental limits on the robustness of image classifiers

Zheng Dai, David Gifford

Robust Graph Dictionary Learning

Weijie Liu, Jiahao Xie, Chao Zhang, Makoto Yamada, Nenggan Zheng

How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization

Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein

Learning Iterative Neural Optimizers for Image Steganography

Xiangyu Chen, Varsha Kishore, Kilian Q Weinberger

SIMPLE: A Gradient Estimator for k-Subset Sampling

Kareem Ahmed, Zhe Zeng, Mathias Niepert, Guy Van den Broeck

Information-Theoretic Diffusion

Xianghao Kong, Rob Brekelmans, Greg Ver Steeg

Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport

Lingkai Kong, Yuqing Wang, Molei Tao

Neural Causal Models for Counterfactual Identification and Estimation

Kevin Muyuan Xia, Yushu Pan, Elias Bareinboim

Replay Memory as An Empirical MDP: Combining Conservative Estimation with Experience Replay

Hongming Zhang, Chenjun Xiao, Han Wang, Jun Jin, Bo Xu

Random Laplacian Features for Learning with Hyperbolic Space

Tao Yu, Christopher De Sa

Transferable Unlearnable Examples

Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun

Supervision Complexity and its Role in Knowledge Distillation

Hrayr Harutyunyan, Ankit Singh Rawat, Aditya Krishna Menon, Seungyeon Kim, Sanjiv Kumar

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

Yihao Feng, Shentao Yang, Shujian Zhang, Jianguo Zhang, Caiming Xiong

A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, Jayant Kalagnanam

Effectively Modeling Time Series with Simple Discrete State Spaces

Michael Zhang, Khaled Kamal Saab, Michael Poli, Tri Dao, Karan Goel

Self-Ensemble Protection: Training Checkpoints Are Good Data Protectors

Sizhe Chen, Geng Yuan, Xinwen Cheng, Yifan Gong, Minghai Qin

Decomposed Prompting: A Modular Approach for Solving Complex Tasks

Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson

Competitive Physics Informed Networks

Qi Zeng, Yash Kothari, Spencer H Bryngelson, Florian Tobias Schaefer

Equal Improvability: A New Fairness Notion Considering the Long-term Impact

Ozgur Guldogan, Yuchen Zeng, Jy-yong Sohn, Ramtin Pedarsani, Kangwook Lee

Composite Slice Transformer: An Efficient Transformer with Composition of Multi-Scale Multi-Range Attentions

Mingu Lee, Saurabh Pitre, Tianyu Jiang, Pierre-David Letourneau, Matthew J Morse

Dual Student Networks for Data-Free Model Stealing

James Beetham, Navid Kardan, Ajmal Saeed Mian, Mubarak Shah

Building Normalizing Flows with Stochastic Interpolants

Michael Samuel Albergo, Eric Vanden-Eijnden

Noise Is Not the Main Factor Behind the Gap Between Sgd and Adam on Transformers, But Sign Descent Might Be

Frederik Kunstner, Jacques Chen, Jonathan Wilder Lavington, Mark Schmidt

A Stable and Scalable Method for Solving Initial Value PDEs with Neural Networks

Marc Anton Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson

A Control-Centric Benchmark for Video Prediction

Stephen Tian, Chelsea Finn, Jiajun Wu

Spotlight: Mobile UI Understanding using Vision-Language Models with a Focus

Gang Li, Yang Li

Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions

Zeyuan Allen-Zhu, Yuanzhi Li

Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning

Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng

Continual Pre-training of Language Models

Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim

SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space

Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, Kostas Daniilidis

A new characterization of the edge of stability based on a sharpness measure aware of batch gradient distribution

Sungyoon Lee, Cheongjae Jang

OPTQ: Accurate Quantization for Generative Pre-trained Transformers

Elias Frantar, Saleh Ashkboos, Torsten Hoefler, Dan Alistarh

Discrete Predictor-Corrector Diffusion Models for Image Synthesis

José Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho

Enhancing Meta Learning via Multi-Objective Soft Improvement Functions

Runsheng Yu, Weiyu Chen, Xinrun Wang, James Kwok

Pruning Deep Neural Networks from a Sparsity Perspective

Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding

Large Language Models are Human-Level Prompt Engineers

Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis

Implicit Regularization for Group Sparsity

Jiangyuan Li, Thanh V Nguyen, Chinmay Hegde, Raymond K. W. Wong

Diffusion-based Image Translation using disentangled style and content representation

Gihyun Kwon, Jong Chul Ye

Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL

Ruiquan Huang, Jing Yang, Yingbin Liang

Avoiding spurious correlations via logit correction

Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal

Broken Neural Scaling Laws

Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger

Adaptive Optimization in the ∞-Width Limit

Etai Littwin, Greg Yang

Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models

Liam H Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja

Unsupervised Learning for Combinatorial Optimization Needs Meta Learning

Haoyu Peter Wang, Pan Li

Reparameterization through Spatial Gradient Scaling

Alexander Detkov, Mohammad Salameh, Muhammad Fetrat, Jialin Zhang, Robin Luwei

Mind the Pool: Convolutional Neural Networks Can Overfit Input Size

Bilal Alsallakh, David Yan, Narine Kokhlikyan, Vivek Miglani, Orion Reblitz-Richardson

Diffusion-GAN: Training GANs with Diffusion

Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou

REPAIR: REnormalizing Permuted Activations for Interpolation Repair

Keller Jordan, Hanie Sedghi, Olga Saukh, Rahim Entezari, Behnam Neyshabur

Compositional Task Representations for Large Language Models

Nan Shao, Zefan Cai, Hanwei Xu, Chonghua Liao, Yanan Zheng

Federated Neural Bandits

Zhongxiang Dai, YAO SHU, Arun Verma, Flint Xiaofeng Fan, Bryan Kian Hsiang Low

Neural Image-based Avatars: Generalizable Radiance Fields for Human Avatar Modeling

Youngjoong Kwon, Dahun Kim, Duygu Ceylan, Henry Fuchs

Interaction-Based Disentanglement of Entities for Object-Centric World Models

Akihiro Nakano, Masahiro Suzuki, Yutaka Matsuo

Simple Emergent Action Representations from Multi-Task Policy Training

Pu Hua, Yubei Chen, Huazhe Xu

Weighted Clock Logic Point Process

Ruixuan Yan, Yunshi Wen, Debarun Bhattacharjya, Ronny Luss, Tengfei Ma

Memorization Capacity of Neural Networks with Conditional Computation

Erdem Koyuncu

Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games

Shicong Cen, Yuejie Chi, Simon Shaolei Du, Lin Xiao

UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph

Jinhao Jiang, Kun Zhou, Xin Zhao, Ji-Rong Wen

Causal Confusion and Reward Misidentification in Preference-Based Reward Learning

Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca Dragan, Daniel S. Brown

Bias Propagation in Federated Learning

Hongyan Chang, Reza Shokri

Neural Bregman Divergences for Distance Learning

Fred Lu, Edward Raff, Francis Ferraro

Replicable Bandits

Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni

Augmentation Component Analysis: Modeling Similarity via the Augmentation Overlaps

Lu Han, Han-Jia Ye, De-Chuan Zhan

Characterizing intrinsic compositionality in transformers with Tree Projections

Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D Manning

Linearly Mapping from Image to Text Space

Jack Merullo, Louis Castricato, Carsten Eickhoff, Ellie Pavlick

Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods

Shunta Akiyama, Taiji Suzuki

PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales

Peifeng Wang, Aaron Chan, Filip Ilievski, Muhao Chen, Xiang Ren

Learning Achievement Structure for Structured Exploration in Domains with Sparse Reward

Zihan Zhou, Animesh Garg

Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning

Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal

The Tilted Variational Autoencoder: Improving Out-of-Distribution Detection

Griffin Floto, Stefan Kremer, Mihai Nica

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions

Jake Snell, Thomas P Zollo, Zhun Deng, Toniann Pitassi, Richard Zemel

HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention

Shijie Geng, Jianbo Yuan, Yu Tian, Yuxiao Chen, Yongfeng Zhang

Over-Training with Mixup May Hurt Generalization

Zixuan Liu, Ziqiao Wang, Hongyu Guo, Yongyi Mao

The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation

Huancheng Chen, Chianing Wang, Haris Vikalo

Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth

Filipe de Avila Belbute-Peres, J Zico Kolter

On the Importance and Applicability of Pre-Training for Federated Learning

Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, Wei-Lun Chao

On Representing Mixed-Integer Linear Programs by Graph Neural Networks

Ziang Chen, Jialin Liu, Xinshang Wang, Wotao Yin

Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization

Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye

Robust Algorithms on Adaptive Inputs from Bounded Adversaries

Yeshwanth Cherapanamjeri, Sandeep Silwal, David Woodruff, Fred Zhang, Qiuyi Zhang

Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks

Jesse Farebrother, Joshua Greaves, Rishabh Agarwal, Charline Le Lan, Ross Goroshin

Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient

Ming Yin, Mengdi Wang, Yu-Xiang Wang

Efficient Deep Reinforcement Learning Requires Regulating Overfitting

Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine

TextShield: Beyond Successfully Detecting Adversarial Sentences in text classification

Lingfeng Shen, Ze Zhang, Haiyun Jiang, Ying Chen

Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms

Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson, Luke Huan

Masked Distillation with Receptive Tokens

Tao Huang, yuan zhang, Shan You, Fei Wang, Chen Qian

Understanding the Covariance Structure of Convolutional Filters

Asher Trockman, Devin Willmott, J Zico Kolter

Auto-Encoding Goodness of Fit

Aaron Palmer, Zhiyi Chi, Derek Aguiar, Jinbo Bi

Recursive Time Series Data Augmentation

Amine Mohamed Aboussalah, Minjae Kwon, Raj G Patel, Cheng Chi, Chi-Guhn Lee

Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought

Abulhair Saparov, He He

Specformer: Spectral Graph Neural Networks Meet Transformers

Deyu Bo, Chuan Shi, Lele Wang, Renjie Liao

CktGNN: Circuit Graph Neural Network for Electronic Design Automation

Zehao Dong, Weidong Cao, Muhan Zhang, Dacheng Tao, Yixin Chen

Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories

Li-Cheng Lan, Huan Zhang, Cho-jui Hsieh

Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis

Weixi Feng, Xuehai He, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula

Neural Systematic Binder

Gautam Singh, Yeongbin Kim, Sungjin Ahn

Editing models with task arithmetic

Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi

What Makes Convolutional Models Great on Long Sequence Modeling?

Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization

Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu

Computational Language Acquisition with Theory of Mind

Andy Liu, Hao Zhu, Emmy Liu, Yonatan Bisk, Graham Neubig

Combinatorial Pure Exploration of Causal Bandits

Nuoya Xiong, Wei Chen

A theoretical study of inductive biases in contrastive learning

Jeff Z. HaoChen, Tengyu Ma

Imitating Graph-Based Planning with Goal-Conditioned Policies

Junsu Kim, Younggyo Seo, Sungsoo Ahn, Kyunghwan Son, Jinwoo Shin