ICML

Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks

Zachary Robertson, Oluwasanmi Koyejo

Comments 19 pages, 7 figures, ICML 2024

Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators

Jianhao Yuan, Francesco Pinto, Adam Davies, Philip Torr

Comments 29 pages, 16 figures

Journal ref ICML 2024

Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization

Emre Sahinoglu, Shahin Shahrampour

Comments To appear in ICML 2024

Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function

Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan

Comments To appear in ICML 2024

Learning to Play Atari in a World of Tokens

Pranav Agarwal, Sheldon Andrews, Samira Ebrahimi Kahou

Comments Accepted at ICML 2024

Scale-Free Image Keypoints Using Differentiable Persistent Homology

Giovanni Barbarani, Francesco Vaccarino, Gabriele Trivigno, Marco Guerra, Gabriele Berton, Carlo Masone

Comments Accepted to ICML 2024

On the Nonlinearity of Layer Normalization

Yunhao Ni, Yuxin Guo, Junlong Jia, Lei Huang

Comments 42 pages, accepted to ICML 2024

Profile Reconstruction from Private Sketches

Hao Wu, Rasmus Pagh

Comments ICML 2024

Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms

Avishek Ghosh, Arya Mazumdar

Comments To appear in ICML 2024

Accelerating Heterogeneous Federated Learning with Closed-form Classifiers

Eros Fanì, Raffaello Camoriano, Barbara Caputo, Marco Ciccone

Comments Accepted at ICML 2024 - https://fed-3r.github.io/

Learning Decision Trees and Forests with Algorithmic Recourse

Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike

Comments 27 pages, 10 figures, to appear in the 41st International Conference on Machine Learning (ICML 2024)

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection

Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han

Comments ICML 2024

Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective

Fabian Falck, Ziyu Wang, Chris Holmes

Comments Accepted at International Conference on Machine Learning (ICML) 2024

Full-Atom Peptide Design based on Multi-modal Flow Matching

Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, Jianzhu Ma

Comments ICML 2024

MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations

Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz, Ni Lao

Comments ICML-2024 Proceedings

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

Comments ICML 2024. Preprint V2 with 17 pages and 5 figures

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

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

Comments Accepted to ICML 2024, 31 pages

Reinformer: Max-Return Sequence Modeling for Offline RL

Zifeng Zhuang, Dengyun Peng, Jinxin Liu, Ziqi Zhang, Donglin Wang

Comments ICML 2024

Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration

Shi-ang Qi, Yakun Yu, Russell Greiner

Comments Accepted to ICML 2024; 37 pages, 19 figures

PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning

Jaejun Lee, Minsung Hwang, Joyce Jiyoung Whang

Comments 32 pages, 3 figures, 4 tables, The 41st International Conference on Machine Learning (ICML 2024)

Why Tabular Foundation Models Should Be a Research Priority

Boris van Breugel, Mihaela van der Schaar

Comments Accepted at International Conference on Machine Learning (ICML 2024)

Position: Do Not Explain Vision Models Without Context

Paulina Tomaszewska, Przemysław Biecek

Comments Accepted at International Conference on Machine Learning (ICML) 2024

Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations

Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li

Comments Published as a conference paper at ICML 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data

Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar

Comments International Conference on Machine Learning (ICML), 2024

Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics

Luca Grillotti, Maxence Faldor, Borja G. León, Antoine Cully

Comments The first two authors contributed equally to this work. Accepted at ICML 2024

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian

Comments ICML 2024 (Oral)

Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis

Juyeon Ko, Inho Kong, Dogyun Park, Hyunwoo J. Kim

Comments ICML 2024

Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning

Long Qian, Juncheng Li, Yu Wu, Yaobo Ye, Hao Fei, Tat-Seng Chua, Yueting Zhuang, Siliang Tang

Comments Accepted by ICML 2024

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

Comments Accepted as an Oral at ICML 2024, Vienna. The first two authors contributed equally

Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast

Xiangming Gu, Xiaosen Zheng, Tianyu Pang, Chao Du, Qian Liu, Ye Wang, Jing Jiang, Min Lin

Comments ICML 2024