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Cryptographic limitations on learning Boolean formulae and finite automata

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Machine Learning: From Theory to Applications

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 661))

This short unrefereed paper has appeared previously in Proceedings of the 21st Annual ACM Symposium on Theory of Computing (ACM, 1989), pages 433–444. The full refereed version of this paper will be published in Jounal of the ACM. The research was done while M. Kearns was at Harvard University, and visiting Oxford University and AT&T Bell Laboratories, and while L. Valiant was visiting Oxford University. M. Kearns was supported by an AT&T Bell Laboratories Ph.D. scholarship, and L.Valiant by grants NSF-DCR-86-00379, ONR-N00014-85-K-0445, DAAL03-86-K-0171 and by SERC.

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Authors and Affiliations

  1. AT&T Bell Laboratories, 600 Mountain Avenue, Room 2A-423, P.O. Box 636, 07974-0636, Murray Hill, New Jersey

    Michael J. Kearns

  2. Aiken Computation Laboratory, Harvard University, 02139, Cambridge, Massachussetts

    Leslie G. Valiant

Authors
  1. Michael J. Kearns
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  2. Leslie G. Valiant
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Stephen José Hanson Werner Remmele Ronald L. Rivest

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© 1993 Springer-Verlag Berlin Heidelberg

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Kearns, M.J., Valiant, L.G. (1993). Cryptographic limitations on learning Boolean formulae and finite automata. In: Hanson, S.J., Remmele, W., Rivest, R.L. (eds) Machine Learning: From Theory to Applications. Lecture Notes in Computer Science, vol 661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56483-7_21

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  • DOI: https://doi.org/10.1007/3-540-56483-7_21

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