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Learning Restricted Models of Arithmetic Circuits
2006
Theory of Computing
We present a polynomial time algorithm for learning a large class of algebraic models of computation. We show that any arithmetic circuit whose partial derivatives induce a low-dimensional vector space is exactly learnable from membership and equivalence queries. As a consequence, we obtain polynomial-time algorithms for learning restricted algebraic branching programs as well as noncommutative set-multilinear arithmetic formulae. In addition, we observe that the algorithms of and Beimel et al.
doi:10.4086/toc.2006.v002a010
dblp:journals/toc/KlivansS06
fatcat:6ddt4sw6g5c7bdy2b3cqnultx4