A consistent and flexible framework for deep matrix factorizations

Author:

De Handschutter PierreORCID,Gillis Nicolas

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference45 articles.

1. Learning the parts of objects by non-negative matrix factorization;Lee;Nature,1999

2. A direct formulation for sparse PCA using semidefinite programming;d’Aspremont;Adv Neural Inf Process Syst,2004

3. Sparse principal component analysis;Zou;J. Comput. Graph. Stat.,2006

4. Dictionary identificationsparse matrix-factorization via ℓ1-minimization;Gribonval;IEEE Trans. Inf. Theory,2010

5. Nonnegative matrix factorization for signal and data analytics: identifiability, algorithms, and applications;Fu;IEEE Signal Process. Mag.,2019

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