Robust Structured Convex Nonnegative Matrix Factorization for Data Representation

Nonnegative Matrix Factorization (NMF) is a popular technique for machine learning. Its power is that it can decompose a nonnegative matrix into two nonnegative factors whose product well approximates the nonnegative matrix. However, the nonnegative constraint of the data matrix limits its applicati...

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Autores principales: Qing Yang, Xuesong Yin, Simin Kou, Yigang Wang
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
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Acceso en línea:https://doaj.org/article/db0a143a19724eb7bfdd940008da7445
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