ICLR 2023

1,573 papers

Learning to reason over visual objects

Shanka Subhra Mondal, Taylor Whittington Webb, Jonathan Cohen

On Pre-training Language Model for Antibody

Danqing Wang, Fei Ye, Hao Zhou

Rethinking Symbolic Regression: Morphology and Adaptability in the Context of Evolutionary Algorithms

Kei Sen Fong, Shelvia Wongso, Mehul Motani

GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks

Xiaoqi Wang, Han Wei Shen

UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining

Hyung Won Chung, Xavier Garcia, Adam Roberts, Yi Tay, Orhan Firat

FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An

Sparse Distributed Memory is a Continual Learner

Trenton Bricken, Xander Davies, Deepak Singh, Dmitry Krotov, Gabriel Kreiman

Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

Yunchong Song, Chenghu Zhou, Xinbing Wang, Zhouhan Lin

Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography

Akarsh Pokkunuru, Pedram Rooshenas, Thilo Strauss, Anuj Abhishek, Taufiquar Khan

TrojText: Test-time Invisible Textual Trojan Insertion

Qian Lou, Yepeng Liu, Bo Feng

Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation

Yannick Hogewind, Thiago D. Simão, Tal Kachman, Nils Jansen

Mid-Vision Feedback

Michael Maynord, Eadom T Dessalene, Cornelia Fermuller, Yiannis Aloimonos

Coupled Multiwavelet Operator Learning for Coupled Differential Equations

Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu

Backpropagation through Combinatorial Algorithms: Identity with Projection Works

Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica, Vít Musil, Volodymyr Kuleshov

Feature selection and low test error in shallow low-rotation ReLU networks

Matus Telgarsky

Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts

Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn

CASR: Generating Complex Sequences with Autoregressive Self-Boost Refinement

Hongwei Han, Mengyu Zhou, Shi Han, Xiu Li, Dongmei Zhang

UL2: Unifying Language Learning Paradigms

Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Jason Wei

Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing

Yu Liu, Mingbo Zhao, Zhao Zhang, Jicong Fan, Yang Lou

Efficient Certified Training and Robustness Verification of Neural ODEs

Mustafa Zeqiri, Mark Niklas Mueller, Marc Fischer, Martin Vechev

MA-BERT: Towards Matrix Arithmetic-only BERT Inference by Eliminating Complex Non-Linear Functions

Neo Wei Ming, Zhehui Wang, Cheng Liu, Rick Siow Mong Goh, Tao Luo

Improving Differentiable Neural Architecture Search by Encouraging Transferability

Parth Sheth, Pengtao Xie

Selective Frequency Network for Image Restoration

Yuning Cui, Yi Tao, Zhenshan Bing, Wenqi Ren, Xinwei Gao

Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement

Michael Chang, Alyssa Li Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine

Regression with Label Differential Privacy

Badih Ghazi, Pritish Kamath, Ravi Kumar, Ethan Leeman, Pasin Manurangsi

Leveraging Large Language Models for Multiple Choice Question Answering

Joshua Robinson, David Wingate

Fast Nonlinear Vector Quantile Regression

Aviv A. Rosenberg, Sanketh Vedula, Yaniv Romano, Alexander Bronstein

Preserving Pre-trained Features Helps Calibrate Fine-tuned Language Models

Guande He, Jianfei Chen, Jun Zhu

RandProx: Primal-Dual Optimization Algorithms with Randomized Proximal Updates

Laurent Condat, Peter Richtarik

Learning in temporally structured environments

Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine Hermann

Protein Sequence and Structure Co-Design with Equivariant Translation

Chence Shi, Chuanrui Wang, Jiarui Lu, Bozitao Zhong, Jian Tang

Gray-Box Gaussian Processes for Automated Reinforcement Learning

Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka

Evolving Populations of Diverse RL Agents with MAP-Elites

Thomas PIERROT, arthur flajolet

Individual Privacy Accounting with Gaussian Differential Privacy

Antti Koskela, Marlon Tobaben, Antti Honkela

LiftedCL: Lifting Contrastive Learning for Human-Centric Perception

Ziwei Chen, Qiang Li, Xiaofeng Wang, Wankou Yang

Confidence-Based Feature Imputation for Graphs with Partially Known Features

Daeho Um, Jiwoong Park, Seulki Park, Jin Young Choi

Asynchronous Distributed Bilevel Optimization

Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian

Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics

Taiji Suzuki, Atsushi Nitanda, Denny Wu

Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation

YAO SHU, Zhongxiang Dai, Weicong Sng, Arun Verma, Patrick Jaillet

A Message Passing Perspective on Learning Dynamics of Contrastive Learning

Yifei Wang, Qi Zhang, Tianqi Du, Jiansheng Yang, Zhouchen Lin

Geometrically regularized autoencoders for non-Euclidean data

Cheongjae Jang, Yonghyeon LEE, Yung-kyun Noh, Frank C. Park

Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules

Jun Xia, Chengshuai Zhao, Bozhen Hu, Zhangyang Gao, Cheng Tan

Actionable Neural Representations: Grid Cells from Minimal Constraints

Will Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington

Behavior Proximal Policy Optimization

Zifeng Zhuang, Kun LEI, Jinxin Liu, Donglin Wang, Yilang Guo

Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study

Mingxu Tao, Yansong Feng, Dongyan Zhao

Iterative Circuit Repair Against Formal Specifications

Matthias Cosler, Frederik Schmitt, Christopher Hahn, Bernd Finkbeiner

Boosting Causal Discovery via Adaptive Sample Reweighting

An Zhang, Fangfu Liu, Wenchang Ma, Zhibo Cai, Xiang Wang

Unveiling the sampling density in non-uniform geometric graphs

Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie

Decision S4: Efficient Sequence-Based RL via State Spaces Layers

Shmuel Bar David, Itamar Zimerman, Eliya Nachmani, Lior Wolf

Cross-Layer Retrospective Retrieving via Layer Attention

Yanwen Fang, Yuxi CAI, Jintai Chen, Jingyu Zhao, Guangjian Tian

Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples

Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen

Don’t fear the unlabelled: safe semi-supervised learning via debiasing

Hugo Schmutz, Olivier HUMBERT, Pierre-Alexandre Mattei

Online Bias Correction for Task-Free Continual Learning

Aristotelis Chrysakis, Marie-Francine Moens

FairGBM: Gradient Boosting with Fairness Constraints

André Cruz, Catarina G Belém, João Bravo, Pedro Saleiro, Pedro Bizarro

CodeBPE: Investigating Subtokenization Options for Large Language Model Pretraining on Source Code

Nadezhda Chirkova, Sergey Troshin

Task-Aware Information Routing from Common Representation Space in Lifelong Learning

Prashant Shivaram Bhat, Bahram Zonooz, Elahe Arani

EquiMod: An Equivariance Module to Improve Visual Instance Discrimination

Alexandre DEVILLERS, Mathieu Lefort

Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning

Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri

LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning

Firas Al-Hafez, Davide Tateo, Oleg Arenz, Guoping Zhao, Jan Peters

WiNeRT: Towards Neural Ray Tracing for Wireless Channel Modelling and Differentiable Simulations

Tribhuvanesh Orekondy, Pratik Kumar, Shreya Kadambi, Hao Ye, Joseph Soriaga

Curriculum-based Co-design of Morphology and Control of Voxel-based Soft Robots

Yuxing Wang, Shuang Wu, Haobo Fu, Qiang Fu, Tiantian Zhang

Solving stochastic weak Minty variational inequalities without increasing batch size

Thomas Pethick, Olivier Fercoq, Puya Latafat, Panagiotis Patrinos, Volkan Cevher

QAID: Question Answering Inspired Few-shot Intent Detection

Asaf Yehudai, Matan Vetzler, Yosi Mass, Koren Lazar, Doron Cohen

Transformer-based model for symbolic regression via joint supervised learning

Wenqiang Li, Weijun Li, Linjun Sun, Min Wu, Lina Yu

Learning Uncertainty for Unknown Domains with Zero-Target-Assumption

Yu Yu, Hassan Sajjad, Jia Xu

Mini-batch k-means terminates within O(d/ε) iterations

Gregory Schwartzman

Softened Symbol Grounding for Neuro-symbolic Systems

Zenan Li, Yuan Yao, Taolue Chen, Jingwei Xu, Chun Cao

Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations

Shuangshuang Chen, Sihao Ding, Yiannis Karayiannidis, Mårten Björkman

Finding Actual Descent Directions for Adversarial Training

Fabian Latorre, Igor Krawczuk, Leello Tadesse Dadi, Thomas Pethick, Volkan Cevher

TVSPrune - Pruning Non-discriminative filters via Total Variation separability of intermediate representations without fine tuning

Chaitanya Murti, Tanay Narshana, Chiranjib Bhattacharyya

DFPC: Data flow driven pruning of coupled channels without data.

Tanay Narshana, Chaitanya Murti, Chiranjib Bhattacharyya

Factorized Fourier Neural Operators

Alasdair Tran, Alexander Mathews, Lexing Xie, Cheng Soon Ong

Quantifying and Mitigating the Impact of Label Errors on Model Disparity Metrics

Julius Adebayo, Melissa Hall, Bowen Yu, Bobbie Chern