HIGHLIGHTS
- who: QING YANG and colleagues from the School of Computer Engineering, Nanjing Institute of Technology, Nanjing, China , Department of Digital Media Technology, Hangzhou Dianzi University, Hangzhou, China have published the Article: Robust Structured Convex Nonnegative Matrix Factorization for Data Representation, in the Journal: (JOURNAL)
- what: The authors propose a novel unsupervised matrix factorization method called Robust Structured Convex Nonnegative Matrix Factorization (RSCNMF). The authors develop an alternate iterative scheme to solve such a new model. MFFS optimizes the following objective function: 2 ρ WTW - I. The authors provide the convergence proof of RSCNMF. n X khi . . .
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