Structured Low-Rank Matrix Factorization: Global Optimality, Algorithms, and Applications.
IEEE Transactions on Pattern Analysis and Machine Intelligence(2020)
摘要
Convex formulations of low-rank matrix factorization problems have received considerable attention in machine learning. However, such formulations often require solving for a matrix of the size of the data matrix, making it challenging to apply them to large scale datasets. Moreover, in many applications the data can display structures beyond simply being low-rank, e.g., images and videos present ...
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关键词
Optimization,Machine learning,Principal component analysis,Videos,Standards,Calcium,Imaging
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