833 research outputs found

    Non-negative mixtures

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    This is the author's accepted pre-print of the article, first published as M. D. Plumbley, A. Cichocki and R. Bro. Non-negative mixtures. In P. Comon and C. Jutten (Ed), Handbook of Blind Source Separation: Independent Component Analysis and Applications. Chapter 13, pp. 515-547. Academic Press, Feb 2010. ISBN 978-0-12-374726-6 DOI: 10.1016/B978-0-12-374726-6.00018-7file: Proof:p\PlumbleyCichockiBro10-non-negative.pdf:PDF owner: markp timestamp: 2011.04.26file: Proof:p\PlumbleyCichockiBro10-non-negative.pdf:PDF owner: markp timestamp: 2011.04.2

    Algorithms for Positive Semidefinite Factorization

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    This paper considers the problem of positive semidefinite factorization (PSD factorization), a generalization of exact nonnegative matrix factorization. Given an mm-by-nn nonnegative matrix XX and an integer kk, the PSD factorization problem consists in finding, if possible, symmetric kk-by-kk positive semidefinite matrices {A1,...,Am}\{A^1,...,A^m\} and {B1,...,Bn}\{B^1,...,B^n\} such that Xi,j=trace(AiBj)X_{i,j}=\text{trace}(A^iB^j) for i=1,...,mi=1,...,m, and j=1,...nj=1,...n. PSD factorization is NP-hard. In this work, we introduce several local optimization schemes to tackle this problem: a fast projected gradient method and two algorithms based on the coordinate descent framework. The main application of PSD factorization is the computation of semidefinite extensions, that is, the representations of polyhedrons as projections of spectrahedra, for which the matrix to be factorized is the slack matrix of the polyhedron. We compare the performance of our algorithms on this class of problems. In particular, we compute the PSD extensions of size k=1+log2(n)k=1+ \lceil \log_2(n) \rceil for the regular nn-gons when n=5n=5, 88 and 1010. We also show how to generalize our algorithms to compute the square root rank (which is the size of the factors in a PSD factorization where all factor matrices AiA^i and BjB^j have rank one) and completely PSD factorizations (which is the special case where the input matrix is symmetric and equality Ai=BiA^i=B^i is required for all ii).Comment: 21 pages, 3 figures, 3 table
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