Independence and port oracles for matroids, with an application to computational learning theory Collette R. Coullard Lisa Hellerstein Article

Received: 12 September 1994 DOI :
10.1007/BF01844845

Cite this article as: Coullard, C.R. & Hellerstein, L. Combinatorica (1996) 16: 189. doi:10.1007/BF01844845
Abstract Given a matroidM with distinguished elemente , aport oracie with respect toe reports whether or not a given subset contains a circuit that containse . The first main result of this paper is an algorithm for computing ane -based ear decomposition (that is, an ear decomposition every circuit of which contains elemente ) of a matroid using only a polynomial number of elementary operations and port oracle calls. In the case thatM is binary, the incidence vectors of the circuits in the ear decomposition form a matrix representation forM . Thus, this algorithm solves a problem in computational learning theory; it learns the class ofbinary matroid port (BMP) functions with membership queries in polynomial time. In this context, the algorithm generalizes results of Angluin, Hellerstein, and Karpinski [1], and Raghavan and Schach [17], who showed that certain subclasses of the BMP functions are learnable in polynomial time using membership queries. The second main result of this paper is an algorithm for testing independence of a given input set of the matroidM . This algorithm, which uses the ear decomposition algorithm as a subroutine, uses only a polynomial number of elementary operations and port oracle calls. The algorithm proves a constructive version of an early theorem of Lehman [13], which states that the port of a connected matroid uniquely determines the matroid.

Mathematics Subject Classification (1991) 05 B 35 68 T 05 68 Q 20 68 Q 25 Research partially funded by NSF PYI Grant No. DDM-91-96083.

Research partially funded by NSF Grant No CCR-92-10957.

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Google Scholar Authors and Affiliations Collette R. Coullard Lisa Hellerstein 1. Department of Industrial Engineering and Management Sciences Northwestern University Evanston USA 2. Department of Electrical Engineering and Computer Science Evanston USA