Can PAC learning algorithms tolerate random attribute noise?
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,General Computer Science
Link
http://link.springer.com/content/pdf/10.1007/BF01300374.pdf
Reference12 articles.
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3. D. Haussler, M. Kearns, N. Littlestone, and M. K. Warmuth. Equivalence of models for polynomial learnability.Information and Computation, 95(2): 129?161, 1991.
4. W. Hoeffding. Probability inequalities for sums of bounded random variables.Journal of the American Statistical Association, 58(301): 13?30, 1963.
5. M. Kearns and Ming Li. Learning in the presence of malicious errors.SIAM Journal of Computing, 22(4): 807?837, 1993.
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