ICML 2023

1,828 papers

On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization

Amir Joudaki, Hadi Daneshmand, Francis Bach

Robust Subtask Learning for Compositional Generalization

Kishor Jothimurugan, Steve Hsu, Osbert Bastani, Rajeev Alur

Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least

Siddharth Joshi, Baharan Mirzasoleiman

On the Expressive Power of Geometric Graph Neural Networks

Chaitanya K. Joshi, Cristian Bodnar, Simon V Mathis, Taco Cohen, Pietro Lió

Automatically Auditing Large Language Models via Discrete Optimization

Erik Jones, Anca Dragan, Aditi Raghunathan, Jacob Steinhardt

R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents

Daniel D. Johnson, Daniel Tarlow, Christian Walder

Thompson Sampling with Less Exploration is Fast and Optimal

Tianyuan Jin, XIANGLIN YANG, Xiaokui Xiao, Pan Xu

Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing

Jikai Jin, Zhiyuan Li, Kaifeng Lyu, Simon Shaolei Du, Jason D. Lee

Effective Structured Prompting by Meta-Learning and Representative Verbalizer

Weisen Jiang, Yu Zhang, James Kwok

NeuralSlice: Neural 3D Triangle Mesh Reconstruction via Slicing 4D Tetrahedral Meshes

Chenbo Jiang, jie Yang, Shwai He, Yu-Kun Lai, Lin Gao

MEWL: Few-shot multimodal word learning with referential uncertainty

Guangyuan Jiang, Manjie Xu, Shiji Xin, Wei Liang, Yujia Peng

Approximate Causal Effect Identification under Weak Confounding

Ziwei Jiang, Lai Wei, Murat Kocaoglu

Learning Unnormalized Statistical Models via Compositional Optimization

Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang

Towards Stable and Efficient Adversarial Training against l_1 Bounded Adversarial Attacks

Yulun Jiang, Chen Liu, Zhichao Huang, Mathieu Salzmann, Sabine Süsstrunk

Detecting Out-of-distribution Data through In-distribution Class Prior

Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu

Online Restless Bandits with Unobserved States

Bowen Jiang, Bo Jiang, Jian Li, Tao LIN, Xinbing Wang

Estimating Causal Effects using a Multi-task Deep Ensemble

Ziyang Jiang, Zhuoran Hou, Yiling Liu, Yiman Ren, Keyu Li

VIMA: Robot Manipulation with Multimodal Prompts

Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou

A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates

Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu

Smooth Non-stationary Bandits

Su Jia, Qian Xie, Nathan Kallus, Peter I. Frazier

Short-lived High-volume Bandits

Su Jia, Nishant Oli, Ian Anderson, Paul Duff, Andrew A Li

Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions

Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou, Jie-Jing Shao, Yuke Xiang

Leveraging Label Non-Uniformity for Node Classification in Graph Neural Networks

Feng Ji, See Hian Lee, Hanyang Meng, KAI ZHAO, Jielong Yang

Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing

Hyeonsu Jeong, Hye Won Chung

BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning

Kishaan Jeeveswaran, Prashant Shivaram Bhat, Bahram Zonooz, Elahe Arani

Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments

Daniel Jarrett, Corentin Tallec, Florent Altché, Thomas Mesnard, Rémi Munos

Unscented Autoencoder

Faris Janjos, Lars Rosenbaum, Maxim Dolgov, J. Marius Zoellner

Learning to Boost Training by Periodic Nowcasting Near Future Weights

Jinhyeok Jang, Woo-Han Yun, Won Hwa Kim, Youngwoo Yoon, Jaehong Kim

Exploring the Benefits of Training Expert Language Models over Instruction Tuning

Joel Jang, Seungone Kim, Seonghyeon Ye, Doyoung Kim, Lajanugen Logeswaran

Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models

Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

Ajay Kumar Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

The Price of Differential Privacy under Continual Observation

Palak Jain, Sofya Raskhodnikova, Satchit Sivakumar, Adam Smith

Multi-Objective GFlowNets

Moksh Jain, Sharath Chandra Raparthy, Alex Hernández-Garcı́a, Jarrid Rector-Brooks, Yoshua Bengio

Unconstrained Online Learning with Unbounded Losses

Andrew Jacobsen, Ashok Cutkosky

Scalable Adaptive Computation for Iterative Generation

Allan Jabri, David J. Fleet, Ting Chen

Efficient Training of Language Models using Few-Shot Learning

Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp, Shankar Krishnan, Satyen Kale

Data-Driven Subgroup Identification for Linear Regression

Zachary Izzo, Ruishan Liu, James Zou

Maximal Initial Learning Rates in Deep ReLU Networks

Gaurav Iyer, Boris Hanin, David Rolnick

DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule

Maor Ivgi, Oliver Hinder, Yair Carmon

CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design

Desi R. Ivanova, Joel Jennings, Tom Rainforth, Cheng Zhang, Adam Foster

Unveiling the Latent Space Geometry of Push-Forward Generative Models

Thibaut Issenhuth, Ugo Tanielian, Jeremie Mary, David Picard

Principled Offline RL in the Presence of Rich Exogenous Information

Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang

Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods

Brian Irwin, Eldad Haber, Raviv Gal, Avi Ziv

Differentially Private Hierarchical Clustering with Provable Approximation Guarantees

Jacob Imola, Alessandro Epasto, Mohammad Mahdian, Vincent Cohen-Addad, Vahab Mirrokni

Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels

Alexander Immer, Tycho F. A. van der Ouderaa, Mark van der Wilk, Gunnar Rätsch, Bernhard Schölkopf

On the Identifiability and Estimation of Causal Location-Scale Noise Models

Alexander Immer, Christoph Schultheiss, Julia E Vogt, Bernhard Schölkopf, Peter Bühlmann

Under-Counted Tensor Completion with Neural Incorporation of Attributes

Shahana Ibrahim, Xiao Fu, Rebecca Hutchinson, Eugene Seo

Information-Theoretic State Space Model for Multi-View Reinforcement Learning

HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-hyeong Kim

MAGANet: Achieving Combinatorial Generalization by Modeling a Group Action

Geonho Hwang, Jaewoong Choi, Hyunsoo Cho, Myungjoo Kang

Combinatorial Neural Bandits

Taehyun Hwang, Kyuwook Chai, Min-hwan Oh

The Impact of Exploration on Convergence and Performance of Multi-Agent Q-Learning Dynamics

Aamal Hussain, Francesco Belardinelli, Dario Paccagnan

One-Shot Federated Conformal Prediction

Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot

SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series

Iris A.M. Huijben, Arthur Andreas Nijdam, Sebastiaan Overeem, Merel M Van Gilst, Ruud Van Sloun

Cut your Losses with Squentropy

Like Hui, Mikhail Belkin, Stephen Wright

Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks

Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola

Federated Linear Contextual Bandits with User-level Differential Privacy

Ruiquan Huang, Huanyu Zhang, Luca Melis, Milan Shen, Meisam Hejazinia

Achieving Linear Speedup in Non-IID Federated Bilevel Learning

Minhui Huang, Dewei Zhang, Kaiyi Ji

Are Large Kernels Better Teachers than Transformers for ConvNets?

Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang

Policy Contrastive Imitation Learning

jialei huang, Zhao-Heng Yin, Yingdong Hu, Yang Gao

NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition

Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao

Theoretical Bounds on the Network Community Profile from Low-rank Semi-definite Programming

Yufan Huang, C. Seshadhri, David F. Gleich

Reparameterized Policy Learning for Multimodal Trajectory Optimization

Zhiao Huang, Litian Liang, Zhan Ling, Xuanlin Li, Chuang Gan

The Power of Uniform Sampling for k-Median

Lingxiao Huang, Shaofeng H.-C. Jiang, Jianing Lou

Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models

Rongjie Huang, Jiawei Huang, Dongchao Yang, Yi Ren, Luping Liu

On Coresets for Clustering in Small Dimensional Euclidean spaces

Lingxiao Huang, Ruiyuan Huang, zengfeng Huang, Xuan Wu

Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning

Taoan Huang, Aaron M Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner

Fast Algorithms for Distributed k-Clustering with Outliers

Junyu Huang, Qilong Feng, Ziyun Huang, Jinhui Xu, Jianxin Wang

Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning

Jiatai Huang, Yan Dai, Longbo Huang

High-dimensional Clustering onto Hamiltonian Cycle

Tianyi Huang, Shenghui Cheng, Stan Z. Li, Zhengjun Zhang

Model-Aware Contrastive Learning: Towards Escaping the Dilemmas

Zizheng Huang, Haoxing Chen, Ziqi Wen, Chao Zhang, Huaxiong Li

Composer: Creative and Controllable Image Synthesis with Composable Conditions

Lianghua Huang, Di Chen, Yu Liu, Yujun Shen, Deli Zhao

Reinforcement Learning in Low-rank MDPs with Density Features

Audrey Huang, Jinglin Chen, Nan Jiang

Understanding the Impact of Adversarial Robustness on Accuracy Disparity

Yuzheng Hu, Fan Wu, Hongyang Zhang, Han Zhao

Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization

Zhengmian Hu, Xidong Wu, Heng Huang

For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal

Yingdong Hu, Renhao Wang, Li Erran Li, Yang Gao

Learning to Learn from APIs: Black-Box Data-Free Meta-Learning

Zixuan Hu, Li Shen, Zhenyi Wang, Baoyuan Wu, Chun Yuan

Surface Snapping Optimization Layer for Single Image Object Shape Reconstruction

Yuan-Ting Hu, Alex Schwing, Raymond A. Yeh

Language Instructed Reinforcement Learning for Human-AI Coordination

Hengyuan Hu, Dorsa Sadigh

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization

Quanqi Hu, Zi-Hao Qiu, Zhishuai Guo, Lijun Zhang, Tianbao Yang

GFlowNet-EM for Learning Compositional Latent Variable Models

Edward J Hu, Nikolay Malkin, Moksh Jain, Katie E Everett, Alexandros Graikos

Omnipredictors for Constrained Optimization

Lunjia Hu, Inbal Rachel Livni Navon, Omer Reingold, Chutong Yang

Tighter Analysis for ProxSkip

Zhengmian Hu, Heng Huang

Thompson Sampling with Diffusion Generative Prior

Yu-Guan Hsieh, Shiva Kasiviswanathan, Branislav Kveton, Patrick Blöbaum

Automatic Data Augmentation via Invariance-Constrained Learning

Ignacio Hounie, Luiz F. O. Chamon, Alejandro Ribeiro

Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits

Yunlong Hou, Vincent Y. F. Tan, Zixin Zhong

Sparse Learning of Dynamical Systems in RKHS: An Operator-Theoretic Approach

Boya Hou, Sina Sanjari, Nathan Dahlin, Subhonmesh Bose, Umesh Vaidya

PromptBoosting: Black-Box Text Classification with Ten Forward Passes

Bairu Hou, Joe O’Connor, Jacob Andreas, Shiyu Chang, Yang Zhang

Decoding Layer Saliency in Language Transformers

Elizabeth Mary Hou, Gregory David Castanon

Approximation Algorithms for Fair Range Clustering

Sedjro Salomon Hotegni, Sepideh Mahabadi, Ali Vakilian

Fair and Accurate Decision Making through Group-Aware Learning

Ramtin Hosseini, Li Zhang, Bhanu Garg, Pengtao Xie

Causal Strategic Classification: A Tale of Two Shifts

Guy Horowitz, Nir Rosenfeld

simple diffusion: End-to-end diffusion for high resolution images

Emiel Hoogeboom, Jonathan Heek, Tim Salimans

Revisiting Data-Free Knowledge Distillation with Poisoned Teachers

Junyuan Hong, Yi Zeng, Shuyang Yu, Lingjuan Lyu, Ruoxi Jia

Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching

Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar

Multi-Task Off-Policy Learning from Bandit Feedback

Joey Hong, Branislav Kveton, Manzil Zaheer, Sumeet Katariya, Mohammad Ghavamzadeh

Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons

Rasmus Høier, D. Staudt, Christopher Zach

AdaBoost is not an Optimal Weak to Strong Learner

Mikael Møller Høgsgaard, Kasper Green Larsen, Martin Ritzert

Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes

Liam Hodgkinson, Chris van der Heide, Fred Roosta, Michael W. Mahoney

Causal Modeling of Policy Interventions From Treatment-Outcome Sequences

Çağlar Hızlı, S. T. John, Anne Tuulikki Juuti, Tuure Tapani Saarinen, Kirsi Hannele Pietiläinen

Generalized Teacher Forcing for Learning Chaotic Dynamics

Florian Hess, Zahra Monfared, Manuel Brenner, Daniel Durstewitz