Results 101 to 110 of about 1,628,183 (185)

Semi-Supervised Nonnegative Matrix Factorization

open access: yes, 2018
Nonnegative matrix factorization (NMF) is a popular method for low-rank approximation of nonnegative matrix, providing a useful tool for representation learning that is valuable for clustering and classification.
Yoo, J, Lee, H, Choi, S
core   +1 more source

Determining Patterns in Neural Activity for Reaching Movements Using Nonnegative Matrix Factorization

open access: yesEURASIP Journal on Advances in Signal Processing, 2005
We propose the use of nonnegative matrix factorization (NMF) as a model-independent methodology to analyze neural activity. We demonstrate that, using this technique, it is possible to identify local spatiotemporal patterns of neural activity in the ...
Nicolelis Miguel AL   +5 more
doaj   +1 more source

Advances in independent component analysis and nonnegative matrix factorization [PDF]

open access: yes, 2009
A fundamental problem in machine learning research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors.
Yuan, Zhijian
core   +1 more source

Sparse Separable Nonnegative Matrix Factorization

open access: yes, 2020
International audienceWe propose a new variant of nonnegative matrix factorization (NMF), combining separability and sparsity assumptions. Separability requires that the columns of the first NMF factor are equal to columns of the input matrix, while ...
Vandaele, Arnaud   +3 more
core  

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