ICML

Long Range Propagation on Continuous-Time Dynamic Graphs

Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio, Davide Bacciu, Claas Grohnfeldt

Comments Accepted at ICML 2024 (https://openreview.net/forum?id=gVg8V9isul)

Journal ref Proceedings of the 41st International Conference on Machine Learning 235 (2024) 16206-16225

Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors

Chun-Yin Huang, Kartik Srinivas, Xin Zhang, Xiaoxiao Li

Comments Paper Accepted at ICML 2024, 23 pages

CNN-JEPA: Self-Supervised Pretraining Convolutional Neural Networks Using Joint Embedding Predictive Architecture

András Kalapos, Bálint Gyires-Tóth

Comments Preprint

Journal ref 2024 International Conference on Machine Learning and Applications (ICMLA), Miami, FL, USA, 2024, pp. 1111-1114

Empowering Tuberculosis Screening with Explainable Self-Supervised Deep Neural Networks

Neel Patel, Alexander Wong, Ashkan Ebadi

Comments 9 pages, 3 figures

Journal ref 2024 International Conference on Machine Learning and Applications (ICMLA), Miami, FL, USA, 2024, pp. 794-797

Using LLMs to Establish Implicit User Sentiment of Software Desirability

Sherri Weitl-Harms, John D. Hastings, Jonah Lum

Comments 6 pages, 2 figures, 2 tables, updated to incorporate feedback

Journal ref 2024 International Conference on Machine Learning and Applications (ICMLA)

A Comparative Analysis of Transformer and LSTM Models for Detecting Suicidal Ideation on Reddit

Khalid Hasan, Jamil Saquer

Comments 23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024 (camera-ready)

Journal ref 2024 International Conference on Machine Learning and Applications (ICMLA)

Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making

Vivek Myers, Chongyi Zheng, Anca Dragan, Sergey Levine, Benjamin Eysenbach

Comments Proceedings of the 41st International Conference on Machine Learning (ICML 2024)

Journal ref Proceedings of the 41st International Conference on Machine Learning (ICML 2024)

BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks

Hamed Poursiami, Ihsen Alouani, Maryam Parsa

Comments 7 pages, 4 figures, 4 tables

Journal ref 2024 International Conference on Machine Learning and Applications (ICMLA), 2024, pp. 705-712

Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method

Qinghua Tao, Francesco Tonin, Alex Lambert, Yingyi Chen, Panagiotis Patrinos, Johan A. K. Suykens

Comments 19 pages, 9 tables, 6 figures

Journal ref the 41st International Conference on Machine Learning (ICML), 2024

Boosting Offline Optimizers with Surrogate Sensitivity

Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:10072-10090, 2024

The Illusion of State in State-Space Models

William Merrill, Jackson Petty, Ashish Sabharwal

Comments To appear at ICML 2024. 9 pages + appendices

Convergence Rates for Softmax Gating Mixture of Experts

Huy Nguyen, Nhat Ho, Alessandro Rinaldo

Comments Section 2 of this work comes from our previous paper titled "On Least Square Estimation in Softmax Gating Mixture of Experts" and published at the ICML 2024

An Efficient Model-Agnostic Approach for Uncertainty Estimation in Data-Restricted Pedometric Applications

Viacheslav Barkov, Jonas Schmidinger, Robin Gebbers, Martin Atzmueller

Comments To be published in the proceedings of ICMLA 2024: 23rd International Conference on Machine Learning and Applications

Learning Surrogates for Offline Black-Box Optimization via Gradient Matching

Minh Hoang, Azza Fadhel, Aryan Deshwal, Janardhan Rao Doppa, Trong Nghia Hoang

Comments Accepted at ICML 2024

Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features

Rodrigo Veiga, Anastasia Remizova, Nicolas Macris

Comments Accepted to ICML 2024

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:49310-49344, 2024

Differentiable Weightless Neural Networks

Alan T. L. Bacellar, Zachary Susskind, Mauricio Breternitz, Eugene John, Lizy K. John, Priscila M. V. Lima, Felipe M. G. França

Journal ref International Conference on Machine Learning (ICML) 2024

Bidirectional Consistency Models

Liangchen Li, Jiajun He

Comments 39 pages, 27 figures; a shorter version of this paper was acceppted at the ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks

Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Celine Lin

Comments Accepted by ICML 2022

Topological Point Cloud Clustering

Vincent P. Grande, Michael T. Schaub

Comments Accepted at the 40th International Conference on Machine Learning (ICML), 2023. Code available at https://git.rwth-aachen.de/netsci/publication-2023-topological-point-cloud-clustering

Journal ref ICML 2023 - 40th International Conference on Machine Learning (ICML)

Adaptive whitening in neural populations with gain-modulating interneurons

Lyndon R. Duong, David Lipshutz, David J. Heeger, Dmitri B. Chklovskii, Eero P. Simoncelli

Comments 20 pages, 10 figures (incl. appendix). To appear in the Proceedings of the 40th International Conference on Machine Learning

Journal ref Proc 40th Int'l Conf on Machine Learning, Honolulu, Hawaii, July 2023

Algebraic Adversarial Attacks on Integrated Gradients

Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew

Comments To appear in the proceedings of the International Conference on Machine Learning and Cybernetics (ICMLC)

Random Latent Exploration for Deep Reinforcement Learning

Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal

Comments Presented at ICML 2024, added link to project website

Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning

Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao

Comments Accepted by ICML 2024

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:6457-6485, 2024

gRNAde: Geometric Deep Learning for 3D RNA inverse design

Chaitanya K. Joshi, Arian R. Jamasb, Ramon Viñas, Charles Harris, Simon V. Mathis, Alex Morehead, Rishabh Anand, Pietro Liò

Comments ICLR 2025 camera-ready version (Spotlight presentation). Previously titled 'Multi-State RNA Design with Geometric Multi-Graph Neural Networks', presented at ICML 2023 Computational Biology Workshop

Overconfident Oracles: Limitations of In Silico Sequence Design Benchmarking

Shikha Surana, Nathan Grinsztajn, Timothy Atkinson, Paul Duckworth, Thomas D. Barrett

Journal ref ICML 2024, AI for Science Workshop

FAIntbench: A Holistic and Precise Benchmark for Bias Evaluation in Text-to-Image Models

Hanjun Luo, Ziye Deng, Ruizhe Chen, Zuozhu Liu

Comments Accepted by ICML DMLR 2024

To the Max: Reinventing Reward in Reinforcement Learning

Grigorii Veviurko, Wendelin Böhmer, Mathijs de Weerdt

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:49455-49470, 2024

IGN : Implicit Generative Networks

Haozheng Luo, Tianyi Wu, Colin Feiyu Han, Zhijun Yan

Comments 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)

PPO-MI: Efficient Black-Box Model Inversion via Proximal Policy Optimization

Xinpeng Shou

Comments 6 pages, submitting to ICML 2025

Towards Hard and Soft Shadow Removal via Dual-Branch Separation Network and Vision Transformer

Jiajia Liang

Comments 11 pages, 5 figures, IEEE International Conference on Machine Learning and Cybernetics (ICMLC) 2024; Currently under review at IEEE