Please use this identifier to cite or link to this item:
http://dspace.mediu.edu.my:8181/xmlui/handle/1721.3/5507| Title: | Statistical Learning: Stability is Sufficient for Generalization and Necessary and Sufficient for Consistency of Empirical Risk Minimization |
| Keywords: | AI Theory of Learning Great Discoveries Consistency ERM Stability |
| Issue Date: | 9-Oct-2013 |
| Description: | 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. revised July 2003 |
| URI: | http://koha.mediu.edu.my:8181/xmlui/handle/1721 |
| Other Identifiers: | AIM-2002-024 CBCL-223 http://hdl.handle.net/1721.3/5507 |
| Appears in Collections: | MIT Items |
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