ICML

Physics-Guided Reinforcement Learning System for Realistic Vehicle Active Suspension Control

Anh N. Nhu, Ngoc-Anh Le, Shihang Li, Thang D. V. Truong

Comments \c{opyright} 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Journal ref 2023 International Conference on Machine Learning and Applications (ICMLA), pp. 422-429

Revisiting Score Function Estimators for $k$-Subset Sampling

Klas Wijk, Ricardo Vinuesa, Hossein Azizpour

Comments ICML 2024 Workshop on Differentiable Almost Everything: Differentiable Relaxations, Algorithms, Operators, and Simulators

Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble

Chenhui Xu, Fuxun Yu, Zirui Xu, Nathan Inkawhich, Xiang Chen

Comments ICML 2024

Indirectly Parameterized Concrete Autoencoders

Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, Hossein Azizpour

Comments ICML 2024

Not Every Image is Worth a Thousand Words: Quantifying Originality in Stable Diffusion

Adi Haviv, Shahar Sarfaty, Uri Hacohen, Niva Elkin-Koren, Roi Livni, Amit H Bermano

Comments GenLaw ICML 2024

Trained Random Forests Completely Reveal your Dataset

Julien Ferry, Ricardo Fukasawa, Timothée Pascal, Thibaut Vidal

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:13545-13569, 2024

Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations

Stefan Sylvius Wagner, Stefan Harmeling

Comments Accepted at the International Conference On Machine Learning (ICML) 2024

Decoder ensembling for learned latent geometries

Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg

Comments International Conference on Machine Learning, ELLIS Workshop on Geometry-grounded Representation Learning and Generative Modeling

Dynamic Metric Embedding into $\ell_p$ Space

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Dariusz R. Kowalski, Jan Olkowski, Max Springer

Comments Accepted to ICML 2024 (15 pages, 3 figures)

Deconstructing the Goldilocks Zone of Neural Network Initialization

Artem Vysogorets, Anna Dawid, Julia Kempe

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR (2024) 235:49717-49732

Agent Instructs Large Language Models to be General Zero-Shot Reasoners

Nicholas Crispino, Kyle Montgomery, Fankun Zeng, Dawn Song, Chenguang Wang

Comments Accepted to ICML 2024

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik, Samir Garibov, Edward Bergman, Frank Hutter

Comments Published at the 41st International Conference on Machine Learning (ICML), Vienna, Austria

Surprisingly Strong Performance Prediction with Neural Graph Features

Gabriela Kadlecová, Jovita Lukasik, Martin Pilát, Petra Vidnerová, Mahmoud Safari, Roman Neruda, Frank Hutter

Comments ICML 2024. Code at https://github.com/gabikadlecova/zc_combine , blog post: https://gabikadlecova.github.io/blog/2024/graf/

How Transformers Learn Causal Structure with Gradient Descent

Eshaan Nichani, Alex Damian, Jason D. Lee

Comments v2: ICML 2024 camera ready

Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity

Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright

Journal ref Proceedings of the International Conference on Machine Learning (ICML) 2024

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs

Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou

Comments Accepted at ICML 2024

A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models

Taehong Moon, Moonseok Choi, EungGu Yun, Jongmin Yoon, Gayoung Lee, Jaewoong Cho, Juho Lee

Comments ICML 2024

Online Matrix Completion: A Collaborative Approach with Hott Items

Dheeraj Baby, Soumyabrata Pal

Comments Appeared at the Forty-first International Conference on Machine Learning, 2024

Mathematical Models of Computation in Superposition

Kaarel Hänni, Jake Mendel, Dmitry Vaintrob, Lawrence Chan

Comments 28 pages, 5 figures. Published at the ICML 2024 Mechanistic Interpretability (MI) Workshop

Causal Representation Learning from Multiple Distributions: A General Setting

Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng

Comments ICML 2024

Few-shot Neural Architecture Search

Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo

Journal ref International Conference on Machine Learning 2021

UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs

Xi Han, Fei Hou, Hong Qin

Comments Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024

Visual Representation Learning with Stochastic Frame Prediction

Huiwon Jang, Dongyoung Kim, Junsu Kim, Jinwoo Shin, Pieter Abbeel, Younggyo Seo

Comments International Conference on Machine Learning (ICML) 2024

Differentiable Annealed Importance Sampling Minimizes The Symmetrized Kullback-Leibler Divergence Between Initial and Target Distribution

Johannes Zenn, Robert Bamler

Comments 22 pages, including 9 pages of main text and 11 pages of appendix, conference paper at ICML 2024, updated terminology

Fast Peer Adaptation with Context-aware Exploration

Long Ma, Yuanfei Wang, Fangwei Zhong, Song-Chun Zhu, Yizhou Wang

Comments ICML 2024. 20 pages

Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection

Dongqi Fu, Yada Zhu, Hanghang Tong, Kommy Weldemariam, Onkar Bhardwaj, Jingrui He

Comments ICML 2024 AI for Science Workshop

Listwise Reward Estimation for Offline Preference-based Reinforcement Learning

Heewoong Choi, Sangwon Jung, Hongjoon Ahn, Taesup Moon

Comments 21 pages, ICML 2024

Towards detailed and interpretable hybrid modeling of continental-scale bird migration

Fiona Lippert, Bart Kranstauber, Patrick Forré, E. Emiel van Loon

Comments AI for Science workshop at ICML 2024

Journal ref AI for Science Workshop at the 41st International Conference on Machine Learning (ICML), 2024

Perturb-and-Project: Differentially Private Similarities and Marginals

Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto, Vahab Mirrokni, Peilin Zhong

Comments 21 ppages, ICML 2024

Dissenting Explanations: Leveraging Disagreement to Reduce Model Overreliance

Omer Reingold, Judy Hanwen Shen, Aditi Talati

Comments V2: AAAI 2024 V1: AI & HCI Workshop at ICML 2023