Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization
Author(s) • • •
Mukherjee, Sayan
Niyogi, Partha
Poggio, Tomaso
Rifkin, Ryan
Date Issued
December 1, 2002
Series/Report no.
AIM-2002-024
CBCL-223
Abstract
Solutions of learning problems by Empirical Risk Minimization (ERM) need to be consistent, so that they may be predictive. They also need to be well-posed, so that they can be used robustly. We show that a statistical form of well-posedness, defined in terms of the key property of L-stability, is necessary and sufficient for consistency of ERM.
Description
revised July 2003
Subjects
AI
Theory of Learning
Great Discoveries
Consistency
ERM
Stability
Persistent DSpace Link