Overview
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics.
Accepted publications
Workshops
ICML 2021 Workshop on Representation Learning for Finance and E-Commerce Applications
July 23
ICML 2021 Workshop on Machine Learning for Data: Automated Creation, Privacy, Bias
July 23
Amazon organizers: Yi Xu, Belinda Zeng
Website: https://icml.cc/Conferences/2021/Schedule?showEvent=8356
Website: https://icml.cc/Conferences/2021/Schedule?showEvent=8356
ICML 2021 Workshop on Reinforcement Learning for Real Life
July 23
ICML 2021 Time Series Workshop
July 24
ICML 2021 International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction
July 24
Tutorials
Responsible AI in Industry: Practical Challenges and Lessons Learned
July 19
Amazon organizers: Krishnaram Kenthapadi, Nashlie Sephus
Website: https://icml.cc/Conferences/2021/Schedule?showEvent=10841
Website: https://icml.cc/Conferences/2021/Schedule?showEvent=10841
Related content
-
July 22, 2022Combining a cutting-edge causal-inference technique and end-to-end machine learning reduces root-mean-square error by 27% to 38%.
-
July 22, 2022Amazon's Bernhard Schölkopf and Dominik Janzing are first and second authors on "breakthrough 2012 paper".
-
July 21, 2022Amazon’s Dominik Janzing on the history and promise of the young field of causal machine learning.
-
July 19, 2022Amazon ICML paper proposes information-theoretic measurement of quantitative causal contribution.