Robust Local Coordinate Non-negative Matrix Factorization via Maximum Correntropy Criteria

Abstract

Non-negative matric factorization (NMF) decomposes a given data matrix X into the product of two lower dimensional non-negative matrices U and V. It has been widely applied in pattern recognition and computer vision because of its simplicity and effectiveness. However, existing NMF methods often fail to learn the sparse representation on high-dimensional… (More)
DOI: 10.1109/SMC.2015.385

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