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Published in: Theory of Computing Systems 2/2014

01-08-2014

Learning Read-Constant Polynomials of Constant Degree Modulo Composites

Authors: Arkadev Chattopadhyay, Ricard Gavaldà, Kristoffer Arnsfelt Hansen, Denis Thérien

Published in: Theory of Computing Systems | Issue 2/2014

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Abstract

Boolean functions that have constant degree polynomial representation over a fixed finite ring form a natural and strict subclass of the complexity class ACC0. They are also precisely the functions computable efficiently by programs over fixed and finite nilpotent groups. This class is not known to be learnable in any reasonable learning model.
In this paper, we provide a deterministic polynomial time algorithm for learning Boolean functions represented by polynomials of constant degree over arbitrary finite rings from membership queries, with the additional constraint that each variable in the target polynomial appears in a constant number of monomials. Our algorithm extends to superconstant but low degree polynomials and still runs in quasipolynomial time.

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Footnotes
1
In an equivalence query, the learning algorithm emits some representation of a Boolean function and receives as answer either a Boolean assignment where it differs from the target function, or “yes” if no such assignment exists.
 
2
Alternatively one could fix the same ordering, say 1,…,n for all monomials. However we find it natural to identify monomials that are identical up to a permutation of the variables.
 
3
A DNF formula is read-k if every variable appears at most k times; a DNF formula is satisfy-j if no assignment satisfies more than j terms simultaneously.
 
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Metadata
Title
Learning Read-Constant Polynomials of Constant Degree Modulo Composites
Authors
Arkadev Chattopadhyay
Ricard Gavaldà
Kristoffer Arnsfelt Hansen
Denis Thérien
Publication date
01-08-2014
Publisher
Springer US
Published in
Theory of Computing Systems / Issue 2/2014
Print ISSN: 1432-4350
Electronic ISSN: 1433-0490
DOI
https://doi.org/10.1007/s00224-013-9488-6

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