Low-Rank Boolean Matrix Approximation by Integer Programming

13 Mar 2018 Reka Kovacs Oktay Gunluk Raphael Hauser

Low-rank approximations of data matrices are an important dimensionality reduction tool in machine learning and regression analysis. We consider the case of categorical variables, where it can be formulated as the problem of finding low-rank approximations to Boolean matrices... (read more)

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