ICML

Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models

Shuchen Meng, Andi Chen, Chihang Wang, Mengyao Zheng, Fangyu Wu, Xupeng Chen, Haowei Ni, Panfeng Li

Comments Accepted by 2024 5th International Conference on Machine Learning and Computer Application

Journal ref Proceedings of the 2024 4th International Conference on Electronic Information Engineering and Computer Science (EIECS), 2024, pp. 892-896

Diverse Concept Proposals for Concept Bottleneck Models

Katrina Brown, Marton Havasi, Finale Doshi-Velez

Comments Accepted to the ICML 2022 Workshop on Human-Machine Collaboration and Teaming

Perfect Alignment May be Poisonous to Graph Contrastive Learning

Jingyu Liu, Huayi Tang, Yong Liu

Comments ICML 24

Theoretical Study of Conflict-Avoidant Multi-Objective Reinforcement Learning

Yudan Wang, Peiyao Xiao, Hao Ban, Kaiyi Ji, Shaofeng Zou

Comments Initial submission at the 41$^{st}$ International Conference on Machine Learning

Technical Report for ICML 2024 TiFA Workshop MLLM Attack Challenge: Suffix Injection and Projected Gradient Descent Can Easily Fool An MLLM

Yangyang Guo, Ziwei Xu, Xilie Xu, YongKang Wong, Liqiang Nie, Mohan Kankanhalli

Comments ICML TiFA Challenge Technical Report

Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts

Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha

Comments The preliminary version of the work appeared in the ICML 2024 Workshop on Foundation Models in the Wild

Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks

Hai-Xiao Wang, Zhichao Wang

Comments Accepted by ICML 2024. The conference version can be accessed via https://openreview.net/forum?id=8m4V6Fx6ma

Linear Adversarial Concept Erasure

Shauli Ravfogel, Michael Twiton, Yoav Goldberg, Ryan Cotterell

Comments Accepted in ICML 2022; a revised version

Embodied CoT Distillation From LLM To Off-the-shelf Agents

Wonje Choi, Woo Kyung Kim, Minjong Yoo, Honguk Woo

Comments Accepted at ICML 2024

Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation

Juntao Dai, Yaodong Yang, Qian Zheng, Gang Pan

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:9872-9903, 2024

LPGD: A General Framework for Backpropagation through Embedded Optimization Layers

Anselm Paulus, Georg Martius, Vít Musil

Comments ICML 2024 conference paper

Journal ref Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024

SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks

Jiwon Song, Kyungseok Oh, Taesu Kim, Hyungjun Kim, Yulhwa Kim, Jae-Joon Kim

Comments ICML 2024

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints

Anselm Paulus, Michal Rolínek, Vít Musil, Brandon Amos, Georg Martius

Comments ICML 2021 conference paper

Journal ref Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event

Causal Action Influence Aware Counterfactual Data Augmentation

Núria Armengol Urpí, Marco Bagatella, Marin Vlastelica, Georg Martius

Comments Accepted in 41st International Conference on Machine Learning (ICML 2024)

Vanilla Bayesian Optimization Performs Great in High Dimensions

Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi

Journal ref International Conference on Machine Learning, 2024

Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control

Arthur Müller, Vishal Rangras, Georg Schnittker, Michael Waldmann, Maxim Friesen, Tobias Ferfers, Lukas Schreckenberg, Florian Hufen, Jürgen Jasperneite, Marco Wiering

Comments Paper was accepted by ICMLA 2021 (20th IEEE International Conference on Machine Learning and Applications). Code available under https://github.com/RL-INA/LemgoRL

In-Context Learning with Topological Information for Knowledge Graph Completion

Udari Madhushani Sehwag, Kassiani Papasotiriou, Jared Vann, Sumitra Ganesh

Journal ref Proceedings of the ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling

Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations

Michael Zhang, Nimit S. Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré

Comments 38 pages, 14 figures. ICML 2022 Long Talk

Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems

Qian Yu, Zhen Xu, Zong Ke

Comments The paper has been accepted by the 2024 6th International Conference on Machine Learning, Big Data and Business Intelligence MLBDBI2024

Relaxed Equivariant Graph Neural Networks

Elyssa Hofgard, Rui Wang, Robin Walters, Tess Smidt

Comments Extended abstract presented at the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at the 41st International Conference on Machine Learning, July 2024, Vienna, Austria

Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality

Yiming Ai, Zhiwei He, Ziyin Zhang, Wenhong Zhu, Hongkun Hao, Kai Yu, Lingjun Chen, Rui Wang

Comments ICML 2024, Large Language Models and Cognition

What Will My Model Forget? Forecasting Forgotten Examples in Language Model Refinement

Xisen Jin, Xiang Ren

Comments ICML 2024 (Spotlight)

Offline Reinforcement Learning via Linear-Programming with Error-Bound Induced Constraints

Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

Comments 47 pages; journal extension of the ICML version with new results

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization

Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal

Comments Accepted at ICML 2024. This is a revised version of arXiv:2306.10486, where we have gone from finite action space to continuous action space, from average iterate convergence to last iterate convergence and from $ε^{-4}$ to $ε^{-3}$ sample complexity. This version fixes the related work result of (Xu et al., 2020a), based on their result update on arXiv

ChemReasoner: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback

Henry W. Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V. Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, Sutanay Choudhury

Comments 9 pages, accepted by ICML 2024, final version

Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion

Yang Cai, Argyris Oikonomou, Weiqiang Zheng

Comments Accepted to ICML 2024. Compared to the last version, a constant term in Theorem 4.1 is improved

Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets

Eleni Straitouri, Suhas Thejaswi, Manuel Gomez Rodriguez

Comments Accepted at the ICML 2024 Workshop on Humans, Algorithmic Decision-Making and Society and published at NeurIPS 2024

COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models

Jinqi Xiao, Miao Yin, Yu Gong, Xiao Zang, Jian Ren, Bo Yuan

Comments ICML 2023 Poster

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:38125-38136, 2023

A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization

Songtao Lu

Comments This work was published in the Proceedings of the Thirty-Ninth International Conference on Machine Learning (ICML 2022)

CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics

Azmine Toushik Wasi, Mst Rafia Islam

Comments 10 Page, 3 Figures. Accepted in: (i) ICML'24: LLMs & Cognition Workshop (Non-archival; OpenReview: https://openreview.net/forum?id=63C9YSc77p) (ii) EMNLP'24 : NLP for Science Workshop (Archival; ACL Anthology: https://aclanthology.org/2024.nlp4science-1.22/)

Journal ref Proceedings of the 1st Workshop on NLP for Science (NLP4Science), EMNLP 2024