Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering

Dimensionality reduction techniques play an essential role in data analytics, signal processing, and machine learning. Dimensionality reduction is usually performed in a preprocessing stage that is separate from subsequent data analysis, such as clustering or classification. Finding reduced-dimensio...

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Vydané v:	IEEE transactions on signal processing Ročník 65; číslo 1; s. 256 - 269
Hlavní autori:	Bo Yang, Xiao Fu, Sidiropoulos, Nicholas D.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.01.2017
Predmet:	Algorithm design and analysis Analytical models clustering Clustering algorithms clustering prior Convergence Data models dimensionality reduction Factor analysis factorial K -means identifiability matrix factorization reduced K -means Signal processing subspace learning Tensile stress tensor factorization
ISSN:	1053-587X, 1941-0476
On-line prístup:	Získať plný text
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