Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent

Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consis...

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Veröffentlicht in:	IEEE transactions on image processing 2011-07, Vol.20 (7), p.2030-2048
Hauptverfasser:	Guan, Naiyang, Tao, Dacheng, Luo, Zhigang, Yuan, Bo
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Biometric Identification Databases, Factual Descent Exact sciences and technology Face Face - anatomy & histology Factorization Gradient descent Humans Image coding Image processing Image Processing, Computer-Assisted - methods Information, signal and communications theory manifold regularization Manifolds Maximization nonnegative matrix factorization (NMF) Optimization Pattern recognition Psychology Representations Signal processing Studies Telecommunications and information theory Vectors
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