Survey of Matrix Completion Models

Chunsheng Liu, Bin Wang, Hong Shan, Shan-shan Li
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Abstract

In recent years, matrix completion (MC), derived from CS, has increasingly become a hot research topic in the field of machine learning. Many researchers have done a large number of fruitful studies on MC. In order to better grasp the development process of MC, the existing matrix completion models (MCMs) are reviewed. First, the process of the evolution from CS to MC is described, illustrating that the development of CS theory has laid the foundation for the formation of MC theory. Second, the existing MCMs are divided into four categories from the perspective of the relaxation of nonconvex and nonsmooth rank function, aiming to provide reasonable solutions for specific matrix completion applications. Finally, the existing problems in current matrix completion technology are pointed out and analyzed, meanwhile possible solutions for these problems are proposed, and the future work is discussed.
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矩阵补全模型综述
近年来,由CS衍生而来的矩阵补全(matrix completion, MC)日益成为机器学习领域的研究热点。许多研究者对矩阵补全模型做了大量卓有成效的研究。为了更好地掌握矩阵补全模型的发展过程,对现有的矩阵补全模型进行了综述。首先,描述了从CS到MC的演变过程,说明CS理论的发展为MC理论的形成奠定了基础。其次,从非凸非光滑秩函数松弛的角度将现有的mcm分为四类,旨在为特定的矩阵补全应用提供合理的解决方案。最后,指出并分析了当前矩阵完井技术中存在的问题,提出了解决这些问题的可行方法,并对今后的工作进行了展望。
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