ICML

The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond

Jiin Woo, Gauri Joshi, Yuejie Chi

Comments Short version at ICML 2023

The Computational Complexity of Concise Hypersphere Classification

Eduard Eiben, Robert Ganian, Iyad Kanj, Sebastian Ordyniak, Stefan Szeider

Comments Short version appeared at ICML 2023

Stellar Spectra Fitting with Amortized Neural Posterior Estimation and nbi

Keming Zhang, Tharindu Jayasinghe, Joshua S. Bloom

Comments Accepted to ICML 2023 Workshop on Machine Learning for Astrophysics. 7 pages 3 figures

The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning

Borja Rodríguez-Gálvez, Arno Blaas, Pau Rodríguez, Adam Goliński, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella

Comments 18 pages: 9 of main text, 2 of references, and 7 of supplementary material [Updated typo in page 6 (Section 3.2)]. Appears in the proceedings of ICML 2023

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

Hongkang Li, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong

Journal ref ICML 2022

Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy

Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy

Journal ref ICML 2023 Workshop on Topology, Algebra, and Geometry in Machine Learning

DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Design

Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab

Journal ref International Conference on Machine Learning, 2023

DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization

Adel Nabli, Edouard Oyallon

Comments International Conference on Machine Learning, Jul 2023, Honolulu, United States

On the Initialization of Graph Neural Networks

Jiahang Li, Yakun Song, Xiang Song, David Paul Wipf

Comments Accepted by ICML 2023

Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimization

Trong Duong, Sang T. Truong, Minh Tam, Bao Bach, Ju-Young Ryu, June-Koo Kevin Rhee

Comments accepted to ICML 2022 Workshop AI4Science

Minimal Random Code Learning with Mean-KL Parameterization

Jihao Andreas Lin, Gergely Flamich, José Miguel Hernández-Lobato

Comments ICML Neural Compression Workshop 2023

Knowledge-based Deep Learning for Modeling Chaotic Systems

Zakaria Elabid, Tanujit Chakraborty, Abdenour Hadid

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

W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting

Lena Sasal, Tanujit Chakraborty, Abdenour Hadid

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

Bayesian Learning with Information Gain Provably Bounds Risk for a Robust Adversarial Defense

Bao Gia Doan, Ehsan Abbasnejad, Javen Qinfeng Shi, Damith C. Ranasinghe

Comments Published at ICML 2022. Code is available at https://github.com/baogiadoan/IG-BNN

Journal ref Proceedings of the 39th International Conference on Machine Learning, PMLR 162:5309-5323, 2022

Interpreting Differentiable Latent States for Healthcare Time-series Data

Yu Chen, Nivedita Bijlani, Samaneh Kouchaki, Payam Barnaghi

Journal ref Workshop on Interpretable ML in Healthcare at International Con- ference on Machine Learning (ICML), Honolulu, Hawaii, USA. 2023

LegendreTron: Uprising Proper Multiclass Loss Learning

Kevin Lam, Christian Walder, Spiridon Penev, Richard Nock

Comments Accepted at the 40th International Conference on Machine Learning (ICML 2023)

Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning

Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang

Comments Project Page: https://www.tongzhouwang.info/quasimetric_rl/ Code: https://github.com/quasimetric-learning/quasimetric-rl/

Journal ref International Conference on Machine Learning (ICML) 2023

Understanding plasticity in neural networks

Clare Lyle, Zeyu Zheng, Evgenii Nikishin, Bernardo Avila Pires, Razvan Pascanu, Will Dabney

Comments Accepted to ICML 2023 (oral presentation)

Mind the box: $l_1$-APGD for sparse adversarial attacks on image classifiers

Francesco Croce, Matthias Hein

Comments In ICML 2021. Fixed typos in Eq. (3) and Eq. (4)

Towards Interpretable Classification of Leukocytes based on Deep Learning

Stefan Röhrl, Johannes Groll, Manuel Lengl, Simon Schumann, Christian Klenk, Dominik Heim, Martin Knopp, Oliver Hayden, Klaus Diepold

Comments Presented at the 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH) @ ICML 2023

The SocialAI School: Insights from Developmental Psychology Towards Artificial Socio-Cultural Agents

Grgur Kovač, Rémy Portelas, Peter Ford Dominey, Pierre-Yves Oudeyer

Comments Preprint, see v1 for a shorter version (accepted at the "Workshop on Theory-of-Mind" at ICML 2023) See project website for demo and code: https://sites.google.com/view/socialai-school

A Variational Autoencoder for Heterogeneous Temporal and Longitudinal Data

Mine Öğretir, Siddharth Ramchandran, Dimitrios Papatheodorou, Harri Lähdesmäki

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

DUET: 2D Structured and Approximately Equivariant Representations

Xavier Suau, Federico Danieli, T. Anderson Keller, Arno Blaas, Chen Huang, Jason Ramapuram, Dan Busbridge, Luca Zappella

Comments Accepted at ICML 2023

A Skew-Sensitive Evaluation Framework for Imbalanced Data Classification

Min Du, Nesime Tatbul, Brian Rivers, Akhilesh Kumar Gupta, Lucas Hu, Wei Wang, Ryan Marcus, Shengtian Zhou, Insup Lee, Justin Gottschlich

Comments 17 pages, Data-centric Machine Learning Research (DMLR) Workshop at ICML 2023

Data Representations' Study of Latent Image Manifolds

Ilya Kaufman, Omri Azencot

Comments Accepted to ICML 2023

UMD: Unsupervised Model Detection for X2X Backdoor Attacks

Zhen Xiang, Zidi Xiong, Bo Li

Comments Proceedings of the 40th International Conference on Machine Learning

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:38013-38038, 2023

Supported Trust Region Optimization for Offline Reinforcement Learning

Yixiu Mao, Hongchang Zhang, Chen Chen, Yi Xu, Xiangyang Ji

Comments Accepted at ICML 2023

Scalable Federated Learning for Clients with Different Input Image Sizes and Numbers of Output Categories

Shuhei Nitta, Taiji Suzuki, Albert Rodríguez Mulet, Atsushi Yaguchi, Ryusuke Hirai

Comments 15 pages, 1 figure, 2023 22nd International Conference on Machine Learning and Applications (ICMLA)

Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic

Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:25254-25274, 2023

PAC-Bayesian Generalization Bounds for Adversarial Generative Models

Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain

Comments Published at ICML 2023