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  5. Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization

Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization

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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
http://hdl.handle.net/1721.3/5507
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