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Tutorial
Mon 9:30 Validity, Reliability, and Significance: A Tutorial on Statistical Methods for Reproducible Machine Learning
Stefan Riezler · Michael Hagmann
Registration Desk
Sun 10:00 Registration Check-in Desk
Tutorial
Mon 13:00 Learning for Interactive Agents
Dorsa Sadigh · Anca Dragan
Tutorial
Mon 10:00 Climate Change and Machine Learning: Opportunities, Challenges, and Considerations
Priya Donti · David Rolnick · Lynn Kaack
Registration Desk
Mon 4:00 Registration Check-in Desk
Tutorial
Mon 12:30 Welcome to the "Big Model" Era: Techniques and Systems to Train and Serve Bigger Models
Hao Zhang · Lianmin Zheng · Zhuohan Li · Ion Stoica
Tutorial
Mon 12:30 Sampling as First-Order Optimization over a space of probability measures
Anna Korba · Adil Salim
Tutorial
Mon 10:00 Bridging Learning and Decision Making
Dylan Foster · Alexander Rakhlin
Tutorial
Mon 9:30 Causality and Deep Learning: Synergies, Challenges and the Future
Nan Rosemary Ke · Stefan Bauer
Tutorial
Mon 15:30 Causal Fairness Analysis
Elias Bareinboim · Drago Plecko
Tutorial
Mon 9:30 Quantitative Reasoning About Data Privacy in Machine Learning
Chuan Guo · Reza Shokri
Poster
Tue 15:30 Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them
Florian Tramer