Overview
Explore a thought-provoking lecture on learning classification metrics from preference feedback, presented by Sanmi Koyejo from Stanford University. Delve into information-theoretic methods for trustworthy machine learning as part of the Simons Institute series. Gain insights into innovative approaches for improving classification accuracy and reliability through the use of preference-based feedback mechanisms. Discover how these techniques can enhance the performance and trustworthiness of machine learning models across various applications.
Syllabus
Learning classification metrics from preference feedback
Taught by
Simons Institute