Abstract
Given an matrix of rank and block of columns inside , we consider the problem of extracting a block of columns of rank which minimize the Hilbert-Schmidt norm of the inverse while preserving the block . This generalizes a previous result of Gluskin-Olevskii, and improves the estimates when given a "good" block .
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