ICML

Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions

Chenyi Zhang, Tongyang Li

Comments 32 pages, 0 figures. To appear in the Fortieth International Conference on Machine Learning (ICML 2023)

Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models

Dongjun Kim, Yeongmin Kim, Se Jung Kwon, Wanmo Kang, Il-Chul Moon

Comments International Conference on Machine Learning (ICML23)

Fair and Optimal Classification via Post-Processing

Ruicheng Xian, Lang Yin, Han Zhao

Comments ICML 2023. Code is at https://github.com/rxian/fair-classification. Comparison to v2: corrected proof of Theorem 4.4

MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose

Yang Fu, Ishan Misra, Xiaolong Wang

Comments ICML 2023 camera ready version. Project page: https://oasisyang.github.io/mononerf

Data Poisoning Attacks Against Multimodal Encoders

Ziqing Yang, Xinlei He, Zheng Li, Michael Backes, Mathias Humbert, Pascal Berrang, Yang Zhang

Comments To Appear in the 40th International Conference on Machine Learning, July 2023

On Investigating the Conservative Property of Score-Based Generative Models

Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, Chun-Yi Lee

Comments ICML 2023

Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions

Alicia Curth, Alihan Hüyük, Mihaela van der Schaar

Comments To appear in the Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, USA. PMLR 202, 2023

Hierarchies of Reward Machines

Daniel Furelos-Blanco, Mark Law, Anders Jonsson, Krysia Broda, Alessandra Russo

Comments Preprint accepted for publication to the 40th International Conference on Machine Learning (ICML-23)

Existence and Estimation of Critical Batch Size for Training Generative Adversarial Networks with Two Time-Scale Update Rule

Naoki Sato, Hideaki Iiduka

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

Error-driven Input Modulation: Solving the Credit Assignment Problem without a Backward Pass

Giorgia Dellaferrera, Gabriel Kreiman

Journal ref Proceedings of the 39th International Conference on Machine Learning 2022

Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization

Ameya Velingker, Maximilian Vötsch, David P. Woodruff, Samson Zhou

Comments ICML 2023

Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space

Anas Barakat, Ilyas Fatkhullin, Niao He

Comments 48 pages, 2 figures, ICML 2023, this paper was initially submitted in January 26th 2023

Journal ref Proceedings of the Fortieth International Conference on Machine Learning (ICML 2023)

Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains

Matthew Dowling, Yuan Zhao, Il Memming Park

Comments Published at ICML 2023

Continual Task Allocation in Meta-Policy Network via Sparse Prompting

Yijun Yang, Tianyi Zhou, Jing Jiang, Guodong Long, Yuhui Shi

Comments Accepted by ICML 2023

Model-agnostic Measure of Generalization Difficulty

Akhilan Boopathy, Kevin Liu, Jaedong Hwang, Shu Ge, Asaad Mohammedsaleh, Ila Fiete

Comments Published at ICML 2023, 28 pages, 6 figures

GFlowNet-EM for learning compositional latent variable models

Edward J. Hu, Nikolay Malkin, Moksh Jain, Katie Everett, Alexandros Graikos, Yoshua Bengio

Comments ICML 2023; code: https://github.com/GFNOrg/GFlowNet-EM

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference

Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault-Levasseur

Comments 15 pages, Accepted at ICML 2023

Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute

Michiel de Jong, Yury Zemlyanskiy, Nicholas FitzGerald, Joshua Ainslie, Sumit Sanghai, Fei Sha, William Cohen

Comments ICML 2023

Learning GFlowNets from partial episodes for improved convergence and stability

Kanika Madan, Jarrid Rector-Brooks, Maksym Korablyov, Emmanuel Bengio, Moksh Jain, Andrei Nica, Tom Bosc, Yoshua Bengio, Nikolay Malkin

Comments ICML 2023

Robust Collaborative Learning with Linear Gradient Overhead

Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan

Comments Accepted paper at ICML 2023

Exploring Chemical Space with Score-based Out-of-distribution Generation

Seul Lee, Jaehyeong Jo, Sung Ju Hwang

Comments ICML 2023

Meta Optimal Transport

Brandon Amos, Samuel Cohen, Giulia Luise, Ievgen Redko

Comments ICML 2023

Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects

Naoufal Acharki, Ramiro Lugo, Antoine Bertoncello, Josselin Garnier

Comments 42 pages, 9 figures, to appear in ICML 2023 conference

Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs

Dale S. Kim, Qing Zhou

Comments 19 pages, 5 figures, to be published in Proceedings of the 40th International Conference on Machine Learning

A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging

Jeffrey Wen, Rizwan Ahmad, Philip Schniter

Comments Accepted to ICML 2023

Probabilistic Concept Bottleneck Models

Eunji Kim, Dahuin Jung, Sangha Park, Siwon Kim, Sungroh Yoon

Comments International Conference on Machine Learning (ICML) 2023

Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables

Rick Wilming, Leo Kieslich, Benedict Clark, Stefan Haufe

Comments Accepted at ICML 2023

Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics

Zonghan Yang, Peng Li, Tianyu Pang, Yang Liu

Comments Accepted at ICML 2023. Our code is available at https://github.com/minicheshire/DEQ-Regulating-Neural-Dynamics

An Effective Meaningful Way to Evaluate Survival Models

Shi-ang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li-Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner

Comments Accepted to ICML 2023

AbODE: Ab Initio Antibody Design using Conjoined ODEs

Yogesh Verma, Markus Heinonen, Vikas Garg

Comments Accepted at ICML 2023