Yoav Freund, Michael Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie  Home/Search
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Abstract: Yoav Freund AT&T Research Murray Hill, NJ 07974 Michael Kearns AT&T Research Murray Hill, NJ 07974 Dana Ron MIT Cambridge, MA 02138 Ronitt Rubinfeld Cornell University Ithaca, NY 14853 Robert E. Schapire AT&T Research Murray Hill, NJ 07974 Linda Sellie University of Chicago Chicago, IL 60637 May 30, 1996 Abstract This paper describes new and efficient algorithms for learning deterministic finite automata. Our approach is primarily distinguished by two features: (1) the... (Update)
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BibTeX entry: (Update)
Y. Freund, M. Kearns, D. Ron, R. Rubinfeld, R. Schapire, and L. Sellie. Efficient learning of typical finite automata from random walks. In Proceedings of the 24th Annual ACM Symposium on Theory of Computing, 1993. http://citeseer.ist.psu.edu/article/freund96efficient.html More
@inproceedings{ freund93efficient,
author = "Yoav Freund and Michael Kearns and Dana Ron and Ronitt Rubinfeld and Robert E. Schapire and Linda Sellie",
title = "Efficient learning of typical finite automata from random walks",
pages = "315--324",
year = "1993",
url = "citeseer.ist.psu.edu/article/freund96efficient.html" }
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