Orthogonal subspace exploration for matrix completion

Hongyuan Zhang, Ziheng Jiao, Xuelong Li

Abstract: Highlights•A tractable orthogonal subspace exploration is designed for matrix completion.•A smooth non-convex surrogate is proposed to replace the classic nuclear norm.•The optimization is proved to converge into the global minimum.•The optimization of surrogate usually converges within dozens of iterations.•The surrogate is expandable so it is still fast with additionl subspace exploration.