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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/db0a143a19724eb7bfdd940008da7445 |
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