ICLR 2023

1,573 papers

Disentangling Learning Representations with Density Estimation

Eric Yeats, Frank Y Liu, Hai Li

Exponential Generalization Bounds with Near-Optimal Rates for L_q-Stable Algorithms

Xiaotong Yuan, Ping Li

FaiREE: fair classification with finite-sample and distribution-free guarantee

Puheng Li, James Zou, Linjun Zhang

TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization

Xiang Li, Junchi Yang, Niao He

Compositional Semantic Parsing with Large Language Models

Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song

Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks

Samyadeep Basu, Megan Stanley, John F Bronskill, Soheil Feizi, Daniela Massiceti

Ollivier-Ricci Curvature for Hypergraphs: A Unified Framework

Corinna Coupette, Sebastian Dalleiger, Bastian Rieck

Equivariant Hypergraph Diffusion Neural Operators

Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li

Liquid Structural State-Space Models

Ramin Hasani, Mathias Lechner, Tsun-Hsuan Wang, Makram Chahine, Alexander Amini

Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting

Mohammad Amin Shabani, Amir H. Abdi, Lili Meng, Tristan Sylvain

A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks

Xinyi Wu, Zhengdao Chen, William Wei Wang, Ali Jadbabaie

Which Layer is Learning Faster? A Systematic Exploration of Layer-wise Convergence Rate for Deep Neural Networks

Yixiong Chen, Alan Yuille, Zongwei Zhou

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Shiwei Liu, Tianlong Chen, Xiaohan Chen, Xuxi Chen, Qiao Xiao

Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses

Xiaolin Hu, Shaojie Li, Yong Liu

Quasi-optimal Reinforcement Learning with Continuous Actions

Yuhan Li, Wenzhuo Zhou, Ruoqing Zhu

Energy-based Out-of-Distribution Detection for Graph Neural Networks

Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan

On the Data-Efficiency with Contrastive Image Transformation in Reinforcement Learning

Sicong Liu, Xi Sheryl Zhang, Yushuo Li, Yifan Zhang, Jian Cheng

Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs

Pihe Hu, Yu Chen, Longbo Huang

Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs

Yu Duan, Zhongfan Jia, Qian Li, Yi Zhong, Kaisheng Ma

AudioGen: Textually Guided Audio Generation

Felix Kreuk, Gabriel Synnaeve, Adam Polyak, Uriel Singer, Alexandre Defossez

Efficient Model Updates for Approximate Unlearning of Graph-Structured Data

Eli Chien, Chao Pan, Olgica Milenkovic

Mitigating Dataset Bias by Using Per-Sample Gradient

Sumyeong Ahn, Seongyoon Kim, Se-Young Yun

LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification

Sharath Girish, Kamal Gupta, Saurabh Singh, Abhinav Shrivastava

Compositional Law Parsing with Latent Random Functions

Fan Shi, Bin Li, Xiangyang Xue

PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs

James Oldfield, Christos Tzelepis, Yannis Panagakis, Mihalis Nicolaou, Ioannis Patras

Learning to CROSS exchange to solve min-max vehicle routing problems

MinJun Kim, Junyoung Park, Jinkyoo Park

Learning Simultaneous Navigation and Construction in Grid Worlds

Wenyu Han, Haoran Wu, Eisuke Hirota, Alexander Gao, Lerrel Pinto

Active Image Indexing

Pierre Fernandez, Matthijs Douze, Herve Jegou, Teddy Furon

Expressive Monotonic Neural Networks

Niklas Nolte, Ouail Kitouni, Mike Williams

Statistical Guarantees for Consensus Clustering

Zhixin Zhou, Gautam Dudeja, Arash A Amini

Extremely Simple Activation Shaping for Out-of-Distribution Detection

Andrija Djurisic, Nebojsa Bozanic, Arjun Ashok, Rosanne Liu

PGrad: Learning Principal Gradients For Domain Generalization

Zhe Wang, Jake Grigsby, Yanjun Qi

Part-Based Models Improve Adversarial Robustness

Chawin Sitawarin, Kornrapat Pongmala, Yizheng Chen, Nicholas Carlini, David Wagner

MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models

Chenglin Yang, Siyuan Qiao, Qihang Yu, Xiaoding Yuan, Yukun Zhu

SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization

Hanseul Cho, Chulhee Yun

Matching receptor to odorant with protein language and graph neural networks

Matej Hladiš, Maxence Lalis, Sebastien Fiorucci, Jérémie Topin

Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions

David Bieber, Rishab Goel, Dan Zheng, Hugo Larochelle, Daniel Tarlow

Boosting Adversarial Transferability using Dynamic Cues

Muzammal Naseer, Ahmad Mahmood, Salman Khan, Fahad Khan

ChordMixer: A Scalable Neural Attention Model for Sequences with Different Length

Ruslan Khalitov, Tong Yu, Lei Cheng, Zhirong Yang

Generalization and Estimation Error Bounds for Model-based Neural Networks

Avner Shultzman, Eyar Azar, Miguel R. D. Rodrigues, Yonina C. Eldar

The Dark Side of AutoML: Towards Architectural Backdoor Search

Ren Pang, Changjiang Li, Zhaohan Xi, Shouling Ji, Ting Wang

Stochastic No-regret Learning for General Games with Variance Reduction

Yichi Zhou, Fang Kong, Shuai Li

Is Attention All That NeRF Needs?

Mukund Varma T, Peihao Wang, Xuxi Chen, Tianlong Chen, Subhashini Venugopalan

Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors

Niv Cohen, Jonathan Kahana, Yedid Hoshen

Calibrating Transformers via Sparse Gaussian Processes

Wenlong Chen, Yingzhen Li

Perfectly Secure Steganography Using Minimum Entropy Coupling

Christian Schroeder de Witt, Samuel Sokota, J Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier

Scaling Laws for a Multi-Agent Reinforcement Learning Model

Oren Neumann, Claudius Gros

Pitfalls of Gaussians as a noise distribution in NCE

Holden Lee, Chirag Pabbaraju, Anish Prasad Sevekari, Andrej Risteski

A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games

Samuel Sokota, Ryan D'Orazio, J Zico Kolter, Nicolas Loizou, Marc Lanctot

Incompatibility Clustering as a Defense Against Backdoor Poisoning Attacks

Charles Jin, Melinda Sun, Martin Rinard

Human-level Atari 200x faster

Steven Kapturowski, Víctor Campos, Ray Jiang, Nemanja Rakicevic, Hado van Hasselt

Efficient Edge Inference by Selective Query

Anil Kag, Igor Fedorov, Aditya Gangrade, Paul Whatmough, Venkatesh Saligrama

Noise Injection Node Regularization for Robust Learning

Noam Itzhak Levi, Itay Mimouni Bloch, Marat Freytsis, Tomer Volansky

Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation

Boah Kim, Yujin Oh, Jong Chul Ye

Discovering Latent Knowledge in Language Models Without Supervision

Collin Burns, Haotian Ye, Dan Klein, Jacob Steinhardt

Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations

Ziyu Jiang, Yinpeng Chen, Mengchen Liu, Dongdong Chen, Xiyang Dai

Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization

Prince Osei Aboagye, YAN ZHENG, Jack Shunn, Chin-Chia Michael Yeh, Junpeng Wang

How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections

Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, Christopher Re

Continuous-time identification of dynamic state-space models by deep subspace encoding

Gerben I. Beintema, Maarten Schoukens, Roland Tóth

Text Summarization with Oracle Expectation

Yumo Xu, Mirella Lapata

MaskViT: Masked Visual Pre-Training for Video Prediction

Agrim Gupta, Stephen Tian, Yunzhi Zhang, Jiajun Wu, Roberto Martín-Martín

Measuring Forgetting of Memorized Training Examples

Matthew Jagielski, Om Thakkar, Florian Tramer, Daphne Ippolito, Katherine Lee

Learning to Segment from Noisy Annotations: A Spatial Correction Approach

Jiachen Yao, Yikai Zhang, Songzhu Zheng, Mayank Goswami, Prateek Prasanna

A Non-monotonic Self-terminating Language Model

Eugene Choi, Kyunghyun Cho, Cheolhyoung Lee

A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova

Characterizing the spectrum of the NTK via a power series expansion

Michael Murray, Hui Jin, Benjamin Bowman, Guido Montúfar

Temporal Dependencies in Feature Importance for Time Series Prediction

Kin Kwan Leung, Clayton Rooke, Jonathan Smith, Saba Zuberi, Maksims Volkovs

AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks

Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec

Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections

Edward De Brouwer, Rahul G Krishnan

Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors

Zeyu Tang, Yatong Chen, Yang Liu, Kun Zhang

SMART: Sentences as Basic Units for Text Evaluation

Reinald Kim Amplayo, Peter J Liu, Yao Zhao, Shashi Narayan

Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness

Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang

Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds

Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon

Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?

Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

Offline Congestion Games: How Feedback Type Affects Data Coverage Requirement

Haozhe Jiang, Qiwen Cui, Zhihan Xiong, Maryam Fazel, Simon Shaolei Du

FedFA: Federated Feature Augmentation

Tianfei Zhou, Ender Konukoglu

Learning Hyper Label Model for Programmatic Weak Supervision

Renzhi Wu, Shen-En Chen, Jieyu Zhang, Xu Chu

Agnostic Learning of General ReLU Activation Using Gradient Descent

Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

The Surprising Computational Power of Nondeterministic Stack RNNs

Brian DuSell, David Chiang

Causal Imitation Learning via Inverse Reinforcement Learning

Kangrui Ruan, Junzhe Zhang, Xuan Di, Elias Bareinboim

Achieving Sub-linear Regret in Infinite Horizon Average Reward Constrained MDP with Linear Function Approximation

Arnob Ghosh, Xingyu Zhou, Ness Shroff

BigVGAN: A Universal Neural Vocoder with Large-Scale Training

Sang-gil Lee, Wei Ping, Boris Ginsburg, Bryan Catanzaro, Sungroh Yoon

Learning Multimodal Data Augmentation in Feature Space

Zichang Liu, Zhiqiang Tang, Xingjian SHI, Aston Zhang, Mu Li

Tuning Frequency Bias in Neural Network Training with Nonuniform Data

Annan Yu, Yunan Yang, Alex Townsend

Variational Latent Branching Model for Off-Policy Evaluation

Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic

PerFedMask: Personalized Federated Learning with Optimized Masking Vectors

Mehdi Setayesh, Xiaoxiao Li, Vincent W.S. Wong

Minimum Description Length Control

Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew Botvinick

MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning

Namyong Park, Ryan A. Rossi, Nesreen Ahmed, Christos Faloutsos

Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts

Rui Wang, Yihe Dong, Sercan O Arik, Rose Yu

Restricted Strong Convexity of Deep Learning Models with Smooth Activations

Arindam Banerjee, Pedro Cisneros-Velarde, Libin Zhu, Misha Belkin

Revisiting the Assumption of Latent Separability for Backdoor Defenses

Xiangyu Qi, Tinghao Xie, Yiming Li, Saeed Mahloujifar, Prateek Mittal

Open-Vocabulary Object Detection upon Frozen Vision and Language Models

Weicheng Kuo, Yin Cui, Xiuye Gu, AJ Piergiovanni, Anelia Angelova

TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs

Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce

Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability

Alex Damian, Eshaan Nichani, Jason D. Lee

Sampling with Mollified Interaction Energy Descent

Lingxiao Li, Qiang Liu, Anna Korba, Mikhail Yurochkin, Justin Solomon

An Extensible Multi-modal Multi-task Object Dataset with Materials

Trevor Scott Standley, Ruohan Gao, Dawn Chen, Jiajun Wu, Silvio Savarese

Constraining Representations Yields Models That Know What They Don't Know

Joao Monteiro, Pau Rodriguez, Pierre-André Noël, Issam H. Laradji, David Vázquez

Concept Gradient: Concept-based Interpretation Without Linear Assumption

Andrew Bai, Chih-Kuan Yeh, Neil Y.C. Lin, Pradeep Kumar Ravikumar, Cho-jui Hsieh

Parameter-Efficient Fine-Tuning Design Spaces

Jiaao Chen, Aston Zhang, Xingjian SHI, Mu Li, Alex Smola

Is a Caption Worth a Thousand Images? A Study on Representation Learning

Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto