Explore the intricacies of federated and collaborative learning in this insightful 55-minute keynote address delivered by Katrina Ligett from Hebrew University. Delve into cutting-edge concepts and methodologies that are shaping the landscape of distributed machine learning. Gain valuable insights into the challenges and opportunities presented by these innovative approaches to data analysis and model training across multiple parties or devices. Discover how federated learning enables privacy-preserving computation while leveraging diverse datasets, and understand the potential applications of collaborative learning in various industries and research domains.
Overview
Syllabus
Keynote
Taught by
Simons Institute
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