Discriminative Multiple Kernel Concept Factorization for Data Representation

Discriminative Multiple Kernel Concept Factorization for Data Representation

Concept Factorization (CF) improves Nonnegative matrix factorization (NMF), which can be only performed in the original data space, by conducting factorization within proper kernel space where the structure of data become much clear than the original data space. CF-based methods have been widely app...

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Bibliografiska uppgifter
Huvudupphovsmän: Lin Mu, Haiying Zhang, Liang Du, Jie Gui, Aidan Li, Xi Zhang
Materialtyp: Artikel
Språk:English
Publicerad: IEEE 2020-01-01
Serie:IEEE Access
Ämnen:
Concept factorization
multiple kernel clustering
local discriminant regularization
data representation
Länkar:https://ieeexplore.ieee.org/document/9205404/

Internet

https://ieeexplore.ieee.org/document/9205404/

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