Efficient learning of typical finite automata from random walks

Yoav Freund, Michael Keams, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations
Original languageEnglish (US)
Title of host publicationProceedings of the 25th Annual ACM Symposium on Theory of Computing, STOC 1993
PublisherAssociation for Computing Machinery
Pages315-324
Number of pages10
ISBN (Electronic)0897915917
DOIs
StatePublished - Jun 1 1993
Event25th Annual ACM Symposium on Theory of Computing, STOC 1993 - San Diego, United States
Duration: May 16 1993May 18 1993

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
VolumePart F129585
ISSN (Print)0737-8017

Other

Other25th Annual ACM Symposium on Theory of Computing, STOC 1993
CountryUnited States
CitySan Diego
Period5/16/935/18/93

All Science Journal Classification (ASJC) codes

  • Software

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  • Cite this

    Freund, Y., Keams, M., Ron, D., Rubinfeld, R., Schapire, R. E., & Sellie, L. (1993). Efficient learning of typical finite automata from random walks. In Proceedings of the 25th Annual ACM Symposium on Theory of Computing, STOC 1993 (pp. 315-324). (Proceedings of the Annual ACM Symposium on Theory of Computing; Vol. Part F129585). Association for Computing Machinery. https://doi.org/10.1145/167088.167191