ICML

Learning Diverse Features in Vision Transformers for Improved Generalization

Armand Mihai Nicolicioiu, Andrei Liviu Nicolicioiu, Bogdan Alexe, Damien Teney

Comments 2023 ICML Workshop on Spurious Correlations, Invariance and Stability

Speech Wikimedia: A 77 Language Multilingual Speech Dataset

Rafael Mosquera Gómez, Julián Eusse, Juan Ciro, Daniel Galvez, Ryan Hileman, Kurt Bollacker, David Kanter

Comments Data-Centric Machine Learning Workshop at the International Machine Learning Conference 2023 (ICML)

EntropyRank: Unsupervised Keyphrase Extraction via Side-Information Optimization for Language Model-based Text Compression

Alexander Tsvetkov, Alon Kipnis

Journal ref ICML 2023 Workshop Neural Compression: From Information Theory to Applications

Machine Learning-guided Lipid Nanoparticle Design for mRNA Delivery

Daisy Yi Ding, Yuhui Zhang, Yuan Jia, Jiuzhi Sun

Comments The 2023 ICML Workshop on Computational Biology

Provable Acceleration of Heavy Ball beyond Quadratics for a Class of Polyak-Łojasiewicz Functions when the Non-Convexity is Averaged-Out

Jun-Kun Wang, Chi-Heng Lin, Andre Wibisono, Bin Hu

Comments (ICML 2022) Proceedings of the 39th International Conference on Machine Learning;

Reinforcement Learning for Sampling on Temporal Medical Imaging Sequences

Zhishen Huang

Comments ICML 2023 Workshop SODS

Predictive Sparse Manifold Transform

Yujia Xie, Xinhui Li, Vince D. Calhoun

Comments Paper presented at the 1st Workshop on High-dimensional Learning Dynamics (HLD) at the 40th International Conference on Machine Learning (ICML) 2023, Honolulu, Hawaii, USA (https://sites.google.com/view/hidimlearning), 10 pages

Go Beyond Imagination: Maximizing Episodic Reachability with World Models

Yao Fu, Run Peng, Honglak Lee

Comments Published in the 40th International Conference on Machine Learning

Discovering Mental Health Research Topics with Topic Modeling

Xin Gao, Cem Sazara

Comments Workshop on Interpretable ML in Healthcare at International Conference on Machine Learning (ICML)

Protecting Language Generation Models via Invisible Watermarking

Xuandong Zhao, Yu-Xiang Wang, Lei Li

Comments ICML 2023

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics

Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, Xuanlong Nguyen, Bo Li, Ding Zhao

Comments 34 pages, 3 figures, 18 tables

Journal ref Proceedings of the 40th International Conference on Machine Learning, PMLR 202:43129-43157, 2023

Overcoming Adversarial Attacks for Human-in-the-Loop Applications

Ryan McCoppin, Marla Kennedy, Platon Lukyanenko, Sean Kennedy

Comments New Frontiers in Adversarial Machine Learning, ICML 2022

Internally Rewarded Reinforcement Learning

Mengdi Li, Xufeng Zhao, Jae Hee Lee, Cornelius Weber, Stefan Wermter

Comments Accepted at ICML 2023. Update: adopt the term "reward model" instead of using "critic" to prevent confusion with the term "critic" in actor-critic algorithms. Project webpage at https://ir-rl.github.io

Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication

Ajay Jaiswal, Shiwei Liu, Tianlong Chen, Ying Ding, Zhangyang Wang

Comments Accepted in ICML 2023. Included comparison with a concurrent work (Jiong et. al. 2023) which independently presents similar ideas, among other SOTA distributed GNN training works

Expectation-Complete Graph Representations with Homomorphisms

Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner

Comments accepted for publication at ICML 2023

An energy-based model for neuro-symbolic reasoning on knowledge graphs

Dominik Dold, Josep Soler Garrido

Comments Accepted for publication at the 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021)

Accelerating Diffusion-based Combinatorial Optimization Solvers by Progressive Distillation

Junwei Huang, Zhiqing Sun, Yiming Yang

Comments Published at ICML 2023, Sampling and Optimization in Discrete Space Workshop. The implementation is at https://github.com/jwrh/Accelerating-Diffusion-based-Combinatorial-Optimization-Solvers-by-Progressive-Distillation

An ML approach to resolution of singularities

Gergely Bérczi, Honglu Fan, Mingcong Zeng

Comments To appear in Proceedings of the 40th International Conference on Machine Learning TAG Workshop (ICML-TAG 2023)

Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images

Weixi Yi, Vasilis Stavrinides, Zachary M. C. Baum, Qianye Yang, Dean C. Barratt, Matthew J. Clarkson, Yipeng Hu, Shaheer U. Saeed

Comments Accepted to MICCAI Workshop MLMI 2023 (14th International Conference on Machine Learning in Medical Imaging)

Spurious Correlations and Where to Find Them

Gautam Sreekumar, Vishnu Naresh Boddeti

Comments 2nd Workshop on SCIS, ICML 2023

Diffusion Models for Black-Box Optimization

Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover

Comments International Conference on Machine Learning 2023

Graph Inductive Biases in Transformers without Message Passing

Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip Torr, Ser-Nam Lim

Comments Published as a conference paper at ICML 2023; 17 pages

Journal ref PMLR 202 (2023) 23321-23337

Half-Hop: A graph upsampling approach for slowing down message passing

Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Veličković, Eva L. Dyer

Comments Published as a conference paper at ICML 2023

Regularizing Adversarial Imitation Learning Using Causal Invariance

Ivan Ovinnikov, Joachim M. Buhmann

Comments Published at the ICML 2023 Workshop on Spurious Correlations, Invariance, and Stability

FeDXL: Provable Federated Learning for Deep X-Risk Optimization

Zhishuai Guo, Rong Jin, Jiebo Luo, Tianbao Yang

Comments International Conference on Machine Learning, 2023

Differentially Private Community Detection for Stochastic Block Models

Mohamed Seif, Dung Nguyen, Anil Vullikanti, Ravi Tandon

Comments ICML 2022. https://proceedings.mlr.press/v162/mohamed22a.html

Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation

Shengcao Cao, Mengtian Li, James Hays, Deva Ramanan, Yi-Xiong Wang, Liang-Yan Gui

Comments ICML 2023

Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models

Phillip Rust, Anders Søgaard

Comments ICML 2023

InGram: Inductive Knowledge Graph Embedding via Relation Graphs

Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang

Comments 14 pages, 4 figures, 6 tables, 40th International Conference on Machine Learning (ICML 2023)

Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection

Marc Lafon, Elias Ramzi, Clément Rambour, Nicolas Thome

Journal ref International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA