(Enter summary)
Abstract: We consider the problem of learning a polynomial over an arbitrary field F
defined on a set of boolean variables. We present the first provably effective algorithm
for exactly identifying such polynomials using membership and equivalence queries.
Our algorithm runs in time polynomial in n, the number of variables, and t, the
number of nonzero terms appearing in the polynomial. The algorithm makes at most
nt + 2 equivalence queries, and at most (nt + 1)(t
+ 3t)=2 membership queries. Our... (Update)
Context of citations to this paper: More
...gave in [Bs94] a technique for learning decision trees under any distribution via the Monotone Theory. Schapire and Sellie gave in [SS93] a Lattice based algorithm for learning multivariate polynomials over the binary field under any distribution. In the former the output...
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BibTeX entry: (Update)
R. E. Schapire and L. M. Sellie. Learning sparse multivariate polynomials over a field with queries and counterexamples. In Proc. of 6th Annu. ACM Workshop on Comput. Learning Theory, pages 17--26, 1993. http://citeseer.ist.psu.edu/schapire96learning.html More
@article{ schapire96learning,
author = "Robert E. Schapire and Linda Sellie",
title = "Learning Sparse Multivariate Polynomials over a Field with Queries and Counterexamples",
journal = "Journal of Computer and System Sciences",
volume = "52",
number = "2",
pages = "201-213",
year = "1996",
url = "citeseer.ist.psu.edu/schapire96learning.html" }
Citations (may not include all citations):
493
Communications of the ACM (context) - Valiant, of et al. - 1984
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Highly resilient correctors for polynomials
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second edition (context) - Herstein, Algebra - 1975
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1
Bulletin of the American Mathematical Society (context) - Wilf, Mobius et al. - 1968
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Advances in Applied Mathematics (context) - Dress, Grabmeier et al. - 1991
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