Computational learning theory: Difference between revisions

Revision as of 15:58, 17 September 2006

Revision as of 15:58, 17 September 2006

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* L. Valiant. A Theory of the Learnable. Communications of the ACM, 27(11):1134--1142, 1984.

===Error tolerance===

* Michael Kearns and Ming Li. Learning in the presence of malicious errors. SIAM Journal on Computing, 22(4):807--837, August 1993. http://citeseer.njist.necpsu.comedu/kearns93learning.html

* Kearns, M. (1993). Efficient noise-tolerant learning from statistical queries. In Proceedings of the Twenty-Fifth Annual ACM Symposium on Theory of Computing, pages 392--401. http://citeseer.njist.necpsu.comedu/kearns93efficient.html

===Equivalence===

* D.Haussler, M.Kearns, N.Littlestone and M.Warmuth, Equivalence of models for polynomial learnability, Proc. 1st ACM Workshop on Computational Learning Theory, (1988) 42-55.