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Efficient Learning of Typical Finite Automata from Random Walks (Extended Abstract) (1996)  (Make Corrections)  (36 citations)
Yoav Freund, Michael Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie



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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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.... We propose a methodology that combines software fault injection at component interfaces [12] and machine learning techniques [2, 7, 9, 10] in an attempt to identify problematic COTS components and understand their anomalous behavior. After a system integrator specifies...

...They give an algorithm for learning finite automata, assuming that the robot has access to a distinguishing sequence. Freund et al. [43] give algorithms for learning typical deterministic finite automata from random walks. Deng and Papadimitriou [35] and Betke [16]...

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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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120   Unbiased bits from sources of weak randomness and probabilis.. - Chor, Goldreich - 1988
109   Inference of finite automata using homing sequences (context) - Rivest, Schapire - 1993
84   Learning when irrelevant attributes abound: A new linear-thr.. (context) - Littlestone - 1988
81   the complexity of minimum inference of regular sets (context) - Angluin - 1978
81   Universal prediction of individual sequences (context) - Feder, Merhav et al. - 1992
59   Prediction-preserving reducibility (context) - Pitt, Warmuth - 1990
57   the learnability of discrete distributions (context) - Kearns, Mansour et al. - 1994
53   Diversity-based inference of finite automata - Rivest, Schapire - 1994
49   functions on randomly drawn points (context) - Haussler, Littlestone et al. - 1994
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48   An Introduction to Probability and its Applications (context) - Feller - 1968
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45   The minimum consistent DFA problem cannot be approximated wi.. (context) - Pitt, Warmuth - 1993
44   Generating quasi-random sequences from semi-random sources (context) - Santha, Vazirani - 1986
42   Finite Automata: Behavior and Synthesis (context) - Trakhtenbrot, Barzdin - 1973
34   the learnability and usage of acyclic probabilistic finite a.. - Ron, Singer et al. - 1995
26   Strong communication complexity or generating quasi-random s.. (context) - Vazirani - 1987
20   System identification via state characterization (context) - Gold - 1972
18   Learning complicated concepts reliably and usefully (context) - Rivest, Sloan - 1988
16   Some tools for approximate 3-coloring (context) - Blum - 1994
9   Biased random walks - Azar, Broder et al. - 1992
3   Deciphering of sequential networks in the absence of an uppe.. (context) - Barzdin - 1970



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