Robust Subspace Clustering via Smoothed Rank Approximation

18 Aug 2015 Zhao Kang Chong Peng Qiang Cheng

Matrix rank minimizing subject to affine constraints arises in many application areas, ranging from signal processing to machine learning. Nuclear norm is a convex relaxation for this problem which can recover the rank exactly under some restricted and theoretically interesting conditions... (read more)

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