2026
Learning Partial Concept Classes and Universal Rates Under Massart Noise
ICML 2026poster
The Massart noise condition is a central model in Probably Approximately Correct (PAC) learning theory. Its importance lies in it being an interpolation condition between realizable and the agnostic settings, under which one can attain faster rates than latter, and, under strict conditions, recover …