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On Weighted Low-Rank Approximation
Published 2 Feb 2013 in stat.AP | (1302.0360v1)
Abstract: Our main interest is the low-rank approximation of a matrix in Rm.n under a weighted Frobenius norm. This norm associates a weight to each of the (m x n) matrix entries. We conjecture that the number of approximations is at most min(m, n). We also investigate how the approximations depend on the weight-values.
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