Low Rank Approximation of Binary Matrices: Column Subset Selection and Generalizations

MFCS, pp. 41:1-41:16, 2018.

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Abstract:

Low rank matrix approximation is an important tool in machine learning. Given a data matrix, low rank approximation helps to find factors, patterns and provides concise representations for the data. Research on low rank approximation usually focus on real matrices. However, in many applications data are binary (categorical) rather than co...More

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