ICML 2024

2,610 papers

Self-Driven Entropy Aggregation for Byzantine-Robust Heterogeneous Federated Learning

Wenke Huang, Zekun Shi, Mang Ye, He Li, Bo Du

On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective

Jincheng Huang, Jialie Shen, Xiaoshuang Shi, Xiaofeng Zhu

MFTN: A Multi-scale Feature Transfer Network Based on IMatchFormer for Hyperspectral Image Super-Resolution

Shuying Huang, Mingyang Ren, Yong Yang, Xiaozheng Wang, Yingzhi Wei

An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series

Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang

Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning

Yizhe Huang, Anji Liu, Fanqi Kong, Yaodong Yang, Song-chun Zhu

Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learning

Zhuo Huang, Chang Liu, Yinpeng Dong, Hang Su, Shibao Zheng

CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks

Yulong Huang, Xiaopeng Lin, Hongwei Ren, Haotian Fu, Yue Zhou

AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios

Zhongzhan Huang, Mingfu Liang, Shanshan Zhong, Liang Lin

Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models

Ding Huang, ting li, Jian Huang

InstructSpeech: Following Speech Editing Instructions via Large Language Models

Rongjie Huang, Ruofan Hu, Yongqi Wang, Zehan Wang, Xize Cheng

In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought

Sili Huang, Jifeng Hu, Hechang Chen, Lichao Sun, Bo Yang

Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL

Jiawei Huang, Niao He, Andreas Krause

DiffDA: a Diffusion model for weather-scale Data Assimilation

Langwen Huang, Lukas Gianinazzi, Yuejiang Yu, Peter Dominik Dueben, Torsten Hoefler

Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion

Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang

Contrastive Predict-and-Search for Mixed Integer Linear Programs

Taoan Huang, Aaron M Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina

Near-Linear Time Approximation Algorithms for k-means with Outliers

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

In-context Convergence of Transformers

Yu Huang, Yuan Cheng, Yingbin Liang

Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games

Kexin Huang, Ziqian Chen, xue wang, Chongming Gao, Jinyang Gao

NeuralIndicator: Implicit Surface Reconstruction from Neural Indicator Priors

Shi-Sheng Huang, Guo Chen, Chen Li Heng, Hua Huang

Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization

Feihu Huang

ReconBoost: Boosting Can Achieve Modality Reconcilement

Cong Hua, Qianqian Xu, Shilong Bao, Zhiyong Yang, Qingming Huang

InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks

Xueyu Hu, Ziyu Zhao, Shuang Wei, Ziwei Chai, Qianli Ma

Accelerating Transformer Pre-training with 2:4 Sparsity

Yuezhou Hu, Kang Zhao, Weiyu Huang, Jianfei Chen, Jun Zhu

High-Performance Temporal Reversible Spiking Neural Networks with O(L) Training Memory and O(1) Inference Cost

JiaKui Hu, Man Yao, Xuerui Qiu, Yuhong Chou, Yuxuan Cai

Bayesian Design Principles for Offline-to-Online Reinforcement Learning

Hao Hu, Yiqin Yang, Jianing Ye, Chengjie Wu, Ziqing Mai

Sparse Model Inversion: Efficient Inversion of Vision Transformers for Data-Free Applications

Zixuan Hu, Yongxian Wei, Li Shen, Zhenyi Wang, Lei Li

Case-Based or Rule-Based: How Do Transformers Do the Math?

Yi Hu, Xiaojuan Tang, Haotong Yang, Muhan Zhang

Provable Privacy with Non-Private Pre-Processing

Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf

Multigroup Robustness

Lunjia Hu, Charlotte Peale, Judy Hanwen Shen

Improving Interpretation Faithfulness for Vision Transformers

Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun

On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis

Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu

Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation

Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo

InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization

Zhengyang Hu, Song Kang, Qunsong Zeng, Kaibin Huang, Yanchao Yang

SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code

Ziniu Hu, Ahmet Iscen, Aashi Jain, Thomas Kipf, Yisong Yue

Accelerated Speculative Sampling Based on Tree Monte Carlo

Zhengmian Hu, Heng Huang

An Information Theoretic Approach to Interaction-Grounded Learning

Xiaoyan Hu, Farzan Farnia, Ho-fung Leung

HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Li Shen, Ya Zhang, Yanfeng Wang

Q-value Regularized Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Chaoqin Huang, Li Shen, Ya Zhang

Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning

Yusong Hu, De Cheng, Dingwen Zhang, Nannan Wang, Tongliang Liu

Outlier-Efficient Hopfield Layers for Large Transformer-Based Models

Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo, Hong-Yu Chen, Weijian Li

Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning

Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns, Chelsea Finn, Jiajun Wu

Careful with that Scalpel: Improving Gradient Surgery with an EMA

Yu-Guan Hsieh, James Thornton, Eugene Ndiaye, Michal Klein, Marco Cuturi

Loss Shaping Constraints for Long-Term Time Series Forecasting

Ignacio Hounie, Javier Porras-Valenzuela, Alejandro Ribeiro

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Charlie Hou, Akshat Shrivastava, Hongyuan Zhan, Rylan Conway, Trang Le

Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang

IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency

Linshan Hou, Ruili Feng, Zhongyun Hua, Wei Luo, Leo Yu Zhang

Efficient Mixture Learning in Black-Box Variational Inference

Alexandra Hotti, Oskar Kviman, Ricky Molén, Vı́ctor Elvira, Jens Lagergren

Multi-Sender Persuasion: A Computational Perspective

Safwan Hossain, Tonghan Wang, Tao LIN, Yiling Chen, David C. Parkes

A Persuasive Approach to Combating Misinformation

Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel

Equilibrium of Data Markets with Externality

Safwan Hossain, Yiling Chen

Recovering the Pre-Fine-Tuning Weights of Generative Models

Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition

Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang

Classification Under Strategic Self-Selection

Guy Horowitz, Yonatan Sommer, Moran Koren, Nir Rosenfeld

Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis

Stefan Horoi, Albert Manuel Orozco Camacho, Eugene Belilovsky, Guy Wolf

Graph Neural PDE Solvers with Conservation and Similarity-Equivariance

Masanobu Horie, NAOTO MITSUME

Weisfeiler Leman for Euclidean Equivariant Machine Learning

Snir Hordan, Tal Amir, Nadav Dym

Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates

Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz

A Primal-Dual Algorithm for Offline Constrained Reinforcement Learning with Linear MDPs

Kihyuk Hong, Ambuj Tewari

Model-based Reinforcement Learning for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

Diversified Batch Selection for Training Acceleration

Feng Hong, Yueming LYU, Jiangchao Yao, Ya Zhang, Ivor Tsang

Enhancing Sufficient Dimension Reduction via Hellinger Correlation

Seungbeom Hong, Ilmun Kim, Jun Song

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie

Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation

Floris Holstege, Bram Wouters, Noud Van Giersbergen, Cees Diks

Criterion Collapse and Loss Distribution Control

Matthew J. Holland

$\bfΦ_\textrmFlow$: Differentiable Simulations for PyTorch, TensorFlow and Jax

Philipp Holl, Nils Thuerey

Verifying message-passing neural networks via topology-based bounds tightening

Christopher Hojny, Shiqiang Zhang, Juan S Campos, Ruth Misener

Two Tales of Single-Phase Contrastive Hebbian Learning

Rasmus Høier, Christopher Zach

Sparse Dimensionality Reduction Revisited

Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen, Jelani Nelson, Chris Schwiegelshohn

Position: Is machine learning good or bad for the natural sciences?

David W Hogg, Soledad Villar

Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems

David T Hoffmann, Simon Schrodi, Jelena Bratulić, Nadine Behrmann, Volker Fischer

Estimating Unknown Population Sizes Using the Hypergeometric Distribution

Liam Hodgson, Danilo Bzdok

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching

Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, Trong Nghia Hoang

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning

Yukinari Hisaki, Isao Ono

Understanding Diffusion Models by Feynman’s Path Integral

Yuji Hirono, Akinori Tanaka, Kenji Fukushima

Balanced Resonate-and-Fire Neurons

Saya Higuchi, Sebastian Kairat, Sander Bohte, Sebastian Otte

Listening to the noise: Blind Denoising with Gibbs Diffusion

David Heurtel-Depeiges, Charles Margossian, Ruben Ohana, Bruno Régaldo-Saint Blancard

Randomized Confidence Bounds for Stochastic Partial Monitoring

Maxime Heuillet, Ola Ahmad, Audrey Durand

Position: Why We Must Rethink Empirical Research in Machine Learning

Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger, Giuseppe Casalicchio, Marcel Wever

Learning Useful Representations of Recurrent Neural Network Weight Matrices

Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber

Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction

Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess, Daniel Durstewitz

Differentially Private Sum-Product Networks

Xenia Heilmann, Mattia Cerrato, Ernst Althaus

DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning

S Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim, Sewoong Oh, Pramod Viswanath

DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems

Kaibo He, Chenhui Zuo, Chengtian Ma, Yanan Sui

Robust Multi-Task Learning with Excess Risks

Yifei He, Shiji Zhou, Guojun Zhang, Hyokun Yun, Yi Xu

SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic

Liulu He, Yufei Zhao, RUI GAO, Yuan Du, Li Du

Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning

Zhiyuan He, Yijun Yang, Pin-Yu Chen, Qiang Xu, Tsung-Yi Ho

Instruction Tuning for Secure Code Generation

Jingxuan He, Mark Vero, Gabriela Krasnopolska, Martin Vechev

Ambiguity-Aware Abductive Learning

Hao-Yuan He, Hui Sun, Zheng Xie, Ming Li

The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks

Songhua He, Periklis A. Papakonstantinou

Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity

Chang He, Zhaoye Pan, Xiao Wang, Bo Jiang

Quantum Algorithm for Online Exp-concave Optimization

Jianhao He, Chengchang Liu, Xutong Liu, Lvzhou Li, John C.S. Lui

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian, Han Yu, Jiashuo Liu

ReDiffuser: Reliable Decision-Making Using a Diffuser with Confidence Estimation

Nantian He, Shaohui Li, Zhi Li, Yu Liu, You He

Distributed Bilevel Optimization with Communication Compression

Yutong He, Jie Hu, Xinmeng Huang, Songtao Lu, Bin Wang

Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation

Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Liwei Wang

Deep Neural Room Acoustics Primitive

Yuhang He, Anoop Cherian, Gordon Wichern, Andrew Markham

From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems

Jianliang He, Siyu Chen, Fengzhuo Zhang, Zhuoran Yang

LoRA+: Efficient Low Rank Adaptation of Large Models

Soufiane Hayou, Nikhil Ghosh, Bin Yu

MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation

Alexandre Hayderi, Amin Saberi, Ellen Vitercik, Anders Wikum