Matches in SemOpenAlex for { <https://semopenalex.org/work/W4220905352> ?p ?o ?g. }
- W4220905352 endingPage "320" @default.
- W4220905352 startingPage "305" @default.
- W4220905352 abstract "Deep Nonnegative Matrix Factorization (Deep NMF) is an effective strategy for feature extraction in recent years. By decomposing the matrix recurrently on account of the NMF algorithms, we obtain a hierarchical neural network structure as well as exploring more interpretable representations of the data. This paper mainly focuses on some theoretical researches with respect to Deep NMF, where the basic models, optimization methods, properties together with its extensions and generalizations are included systematically. We partition the Deep NMF algorithms into five categories: Deep NMF, Constrained Deep NMF, Generalized Deep NMF, Multi-View Deep Matrix Factorization (MF), the association between deep neural network (DNN) and NMF. Besides, we investigate the clustering performance of Deep NMF Algorithms on some face databases. Then the design principles, major steps, relationships, application domains and evolution of Deep NMF methods are comprehensively analyzed. Moreover, some open problems of Deep NMF are discussed." @default.
- W4220905352 created "2022-04-03" @default.
- W4220905352 creator A5016707818 @default.
- W4220905352 creator A5028877617 @default.
- W4220905352 creator A5053712480 @default.
- W4220905352 date "2022-06-01" @default.
- W4220905352 modified "2023-09-30" @default.
- W4220905352 title "A survey of deep nonnegative matrix factorization" @default.
- W4220905352 cites W1504438288 @default.
- W4220905352 cites W1565719317 @default.
- W4220905352 cites W1587285176 @default.
- W4220905352 cites W1902027874 @default.
- W4220905352 cites W1964412262 @default.
- W4220905352 cites W1970352604 @default.
- W4220905352 cites W1978201669 @default.
- W4220905352 cites W1981626846 @default.
- W4220905352 cites W1982828652 @default.
- W4220905352 cites W1986451263 @default.
- W4220905352 cites W1991380130 @default.
- W4220905352 cites W2002519017 @default.
- W4220905352 cites W2008708467 @default.
- W4220905352 cites W2016293853 @default.
- W4220905352 cites W2017288758 @default.
- W4220905352 cites W2019149505 @default.
- W4220905352 cites W2025630051 @default.
- W4220905352 cites W2026034143 @default.
- W4220905352 cites W2029786966 @default.
- W4220905352 cites W2039844283 @default.
- W4220905352 cites W2040311714 @default.
- W4220905352 cites W2047779269 @default.
- W4220905352 cites W2051061727 @default.
- W4220905352 cites W2058232500 @default.
- W4220905352 cites W2058406265 @default.
- W4220905352 cites W2059048018 @default.
- W4220905352 cites W2059085244 @default.
- W4220905352 cites W2064733273 @default.
- W4220905352 cites W2065350495 @default.
- W4220905352 cites W2069317438 @default.
- W4220905352 cites W2070485440 @default.
- W4220905352 cites W2072026894 @default.
- W4220905352 cites W2072329731 @default.
- W4220905352 cites W2077055938 @default.
- W4220905352 cites W2077799289 @default.
- W4220905352 cites W2082445317 @default.
- W4220905352 cites W2090123586 @default.
- W4220905352 cites W2090341258 @default.
- W4220905352 cites W2091334405 @default.
- W4220905352 cites W2092612387 @default.
- W4220905352 cites W2102536337 @default.
- W4220905352 cites W2103559027 @default.
- W4220905352 cites W2104762657 @default.
- W4220905352 cites W2104819583 @default.
- W4220905352 cites W2106442491 @default.
- W4220905352 cites W2106789617 @default.
- W4220905352 cites W2108433027 @default.
- W4220905352 cites W2110096996 @default.
- W4220905352 cites W2121123096 @default.
- W4220905352 cites W2121647436 @default.
- W4220905352 cites W2129354191 @default.
- W4220905352 cites W2138451337 @default.
- W4220905352 cites W2142584058 @default.
- W4220905352 cites W2144015117 @default.
- W4220905352 cites W2144719328 @default.
- W4220905352 cites W2146739705 @default.
- W4220905352 cites W2146913572 @default.
- W4220905352 cites W2150248355 @default.
- W4220905352 cites W2153335355 @default.
- W4220905352 cites W2154209978 @default.
- W4220905352 cites W2155151262 @default.
- W4220905352 cites W2167732364 @default.
- W4220905352 cites W2168103112 @default.
- W4220905352 cites W2168143240 @default.
- W4220905352 cites W2197404611 @default.
- W4220905352 cites W2294040673 @default.
- W4220905352 cites W2320751516 @default.
- W4220905352 cites W2327699058 @default.
- W4220905352 cites W2510237014 @default.
- W4220905352 cites W2523237497 @default.
- W4220905352 cites W2526561371 @default.
- W4220905352 cites W2546239132 @default.
- W4220905352 cites W2555164456 @default.
- W4220905352 cites W2561981131 @default.
- W4220905352 cites W2583956757 @default.
- W4220905352 cites W2603699330 @default.
- W4220905352 cites W2605146283 @default.
- W4220905352 cites W2605997226 @default.
- W4220905352 cites W2611719608 @default.
- W4220905352 cites W2758049963 @default.
- W4220905352 cites W2766640142 @default.
- W4220905352 cites W2790808809 @default.
- W4220905352 cites W2809386270 @default.
- W4220905352 cites W2810535283 @default.
- W4220905352 cites W2888062967 @default.
- W4220905352 cites W2893348249 @default.
- W4220905352 cites W2897979119 @default.
- W4220905352 cites W2909648691 @default.
- W4220905352 cites W2939782843 @default.
- W4220905352 cites W2964144157 @default.