Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent

By Naiyang Guan, Dacheng Tao, Zhigang Luo, Bo Yuan. IEEE Transactions on Image Processing, 2011

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NeNMF: An Optimal Gradient Method for Nonnegative Matrix Factorization (2012, background): “[10], [11] proposed to accelerate MUR by searching each matrix factor along its rescaled gradient direction with the optimal step length.”
3-D Object Retrieval and Recognition With Hypergraph Analysis (2012, methodology): “There are many existing nonnegative matrix factorization methods, such as in [50]–[52].”
Nonnegative Matrix Factorization: A Comprehensive Review (2013, unknown): “Discriminant Sparse NMF [105], Manifold-respecting Discriminant NMF [106], and Manifold Regularized Discriminative NMF [107] are appropriate illustrations of the notion of integrating different constraints, so as to achieve better decomposition quality reflecting the multilateral characteristics of ”