ICML 2022 Schedule

Tutorial

Mon Jul 18 10:30 PM -- 12:45 AM (KST) @ Room 307 None

Validity, Reliability, and Significance: A Tutorial on Statistical Methods for Reproducible Machine Learning

Stefan Riezler · Michael Hagmann

Tutorial

Mon Jul 18 10:30 PM -- 12:30 AM (KST) @ Hall F None

Causality and Deep Learning: Synergies, Challenges and the Future

Nan Rosemary Ke · Stefan Bauer

Tutorial

Mon Jul 18 10:30 PM -- 12:30 AM (KST) @ Ballroom 1 & 2 None

Quantitative Reasoning About Data Privacy in Machine Learning

Chuan Guo · Reza Shokri

Tutorial

Tue Jul 19 02:00 AM -- 04:00 AM (KST) @ Ballroom 1 & 2 None

Bridging Learning and Decision Making

Dylan Foster · Alexander Rakhlin

Tutorial

Tue Jul 19 02:00 AM -- 04:00 AM (KST) @ Hall F None

Learning for Interactive Agents

Dorsa Sadigh · Anca Dragan

Tutorial

Tue Jul 19 02:00 AM -- 04:00 AM (KST) @ Room 307 None

Climate Change and Machine Learning: Opportunities, Challenges, and Considerations

Priya Donti · David Rolnick · Lynn Kaack

Tutorial

Tue Jul 19 04:30 AM -- 06:30 AM (KST) @ Ballroom 1 & 2 None

Sampling as First-Order Optimization over a space of probability measures

Anna Korba · Adil Salim

Tutorial

Tue Jul 19 04:30 AM -- 06:30 AM (KST) @ Room 307 None

Causal Fairness Analysis

Elias Bareinboim · Drago Plecko

Tutorial

Tue Jul 19 04:30 AM -- 06:50 AM (KST) @ Hall F None

Welcome to the "Big Model" Era: Techniques and Systems to Train and Serve Bigger Models

Hao Zhang · Lianmin Zheng · Zhuohan Li · Ion Stoica

Query	Result
Kernel	Current meeting year events with kernel in the abstract, author names, room location, date, or abstract
Deep Learning	Deep or Learning
"Deep Learning"	Deep Learning
@"Boston University"	Search for "Boston University" but only in the Institution and email fields of authors. Prefix a search term with the @ symbol to constrain it to just email and institution.