ICML

GATE: How to Keep Out Intrusive Neighbors

Nimrah Mustafa, Rebekka Burkholz

Comments 26 pages. Published at the International Conference on Machine Learning (ICML), 2024

RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models

Qi Lv, Hao Li, Xiang Deng, Rui Shao, Michael Yu Wang, Liqiang Nie

Comments Accepted by ICML 2024; Project page: https://aopolin-lv.github.io/RoboMP2.github.io/

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:33558-33574, 2024

C-RAG: Certified Generation Risks for Retrieval-Augmented Language Models

Mintong Kang, Nezihe Merve Gürel, Ning Yu, Dawn Song, Bo Li

Comments Accepted to ICML 2024

ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data

Carmen Martin-Turrero, Maxence Bouvier, Manuel Breitenstein, Pietro Zanuttigh, Vincent Parret

Comments Originally published in the Proceedings of Machine Learning Research ICML 2024

Journal ref Proceedings of the 41st International Conference on Machine Learning (2024), in Proceedings of Machine Learning Research 235:48837-48854

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter

Comments ICML 2024 Oral; Project webpage: https://chain-of-code.github.io

SAPG: Split and Aggregate Policy Gradients

Jayesh Singla, Ananye Agarwal, Deepak Pathak

Comments In ICML 2024 (Oral). Website at https://sapg-rl.github.io/

GraphBPE: Molecular Graphs Meet Byte-Pair Encoding

Yuchen Shen, Barnabás Póczos

Comments accepted by ICML 2024 AI for Science Workshop

Fairness Through Controlled (Un)Awareness in Node Embeddings

Dennis Vetter, Jasper Forth, Gemma Roig, Holger Dell

Comments Poster at ICML 2024 Workshop on the Next Generation of AI Safety

Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment

Max Wilcoxson, Morten Svendgård, Ria Doshi, Dylan Davis, Reya Vir, Anant Sahai

Comments ICML Workshop on In-Context Learning

Unfolding Time: Generative Modeling for Turbulent Flows in 4D

Abdullah Saydemir, Marten Lienen, Stephan Günnemann

Comments AI4Science Workshop @ ICML 2024

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting

Andrei Margeloiu, Adrián Bazaga, Nikola Simidjievski, Pietro Liò, Mateja Jamnik

Comments Presented at 1st ICML Workshop on In-Context Learning (ICL @ ICML 2024)

Injecting Hierarchical Biological Priors into Graph Neural Networks for Flow Cytometry Prediction

Fatemeh Nassajian Mojarrad, Lorenzo Bini, Thomas Matthes, Stéphane Marchand-Maillet

Comments 14 pages, ICML Conference Workshop 2024. arXiv admin note: text overlap with arXiv:2402.18610

Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks

Zirou Qiu, Abhijin Adiga, Madhav V. Marathe, S. S. Ravi, Daniel J. Rosenkrantz, Richard E. Stearns, Anil Vullikanti

Comments Accepted at ICML 2024

Position: Explain to Question not to Justify

Przemyslaw Biecek, Wojciech Samek

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:3996-4006, 2024

Privacy-preserving data release leveraging optimal transport and particle gradient descent

Konstantin Donhauser, Javier Abad, Neha Hulkund, Fanny Yang

Comments Published at the Forty-first International Conference on Machine Learning

Understanding Unimodal Bias in Multimodal Deep Linear Networks

Yedi Zhang, Peter E. Latham, Andrew Saxe

Comments ICML 2024 camera ready

Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding

Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee

Comments ES-FoMo Workshop at ICML 2023 / Published in TMLR

FADAS: Towards Federated Adaptive Asynchronous Optimization

Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen

Comments Accepted by ICML 2024

Explaining the Model, Protecting Your Data: Revealing and Mitigating the Data Privacy Risks of Post-Hoc Model Explanations via Membership Inference

Catherine Huang, Martin Pawelczyk, Himabindu Lakkaraju

Comments ICML 2024 Workshop on the Next Generation of AI Safety

Synthetic Data, Similarity-based Privacy Metrics, and Regulatory (Non-)Compliance

Georgi Ganev

Comments Accepted to the 2nd Workshop on Generative AI and Law (GenLaw 2024), part of ICML 2024

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains

Junhong Shen, Neil Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolo Fusi

Comments ICML 2024

Gene Regulatory Network Inference from Pre-trained Single-Cell Transcriptomics Transformer with Joint Graph Learning

Sindhura Kommu, Yizhi Wang, Yue Wang, Xuan Wang

Comments Accepted into the ICML 2024 AI for Science workshop

Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization

Feihu Huang

Comments ICML 2024 (Oral). arXiv admin note: text overlap with arXiv:2311.04520

SDLNet: Statistical Deep Learning Network for Co-Occurring Object Detection and Identification

Binay Kumar Singh, Niels Da Vitoria Lobo

Comments 8 pages, 3 figures, ICMLT-2024. arXiv admin note: text overlap with arXiv:2403.17223

Journal ref (ICMLT 2024) 2024 9th International Conference on Machine Learning Technologies

Learning from Memory: Non-Parametric Memory Augmented Self-Supervised Learning of Visual Features

Thalles Silva, Helio Pedrini, Adín Ramírez Rivera

Comments To appear in ICML 2024. Code at https://github.com/sthalles/MaSSL

Expressivity and Generalization: Fragment-Biases for Molecular GNNs

Tom Wollschläger, Niklas Kemper, Leon Hetzel, Johanna Sommer, Stephan Günnemann

Journal ref International Conference on Machine Learning. 2024. Oral

Diagnosing and fixing common problems in Bayesian optimization for molecule design

Austin Tripp, José Miguel Hernández-Lobato

Comments 8 pages, 4 figures. ICML 2024 AI for science workshop (https://openreview.net/forum?id=V4aG4wsoIt). Code at: https://github.com/AustinT/basic-mol-bo-workshop2024

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Haoran You, Yichao Fu, Zheng Wang, Amir Yazdanbakhsh, Yingyan Celine Lin

Comments Accepted by ICML 2024; 17 pages; 10 figures; 16 tables

Nonparametric extensions of randomized response for private confidence sets

Ian Waudby-Smith, Zhiwei Steven Wu, Aaditya Ramdas

Comments 50 pages, 7 figures, to appear in the 2023 International Conference on Machine Learning with an Oral Presentation

Scalify: scale propagation for efficient low-precision LLM training

Paul Balança, Sam Hosegood, Carlo Luschi, Andrew Fitzgibbon

Comments 11 pages, 5 figures, ICML 2024 WANT workshop