NMFLibrary: Non-negative Matrix Factorization (NMF) Library: Version 2.1

X. Wang, Y. Zhong, L. Zhang, and Y. Xu, “Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 11, pp.6287-6304, 2017.

Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph Clustering

Texture synthesis based on sparse representation.

Source code for the paper titled "Towards Weak Signal Analysis in Hyperspectral Data: A Semi-supervised Unmixing Perspective"

Toolbox allows to test and compare methods for Image Completion and Data Completion problems in Matlab. Presented methods use various Nonnegative Matrix Factorization and Tensor decomposition algorithms. It was based on research performed during realization of PhD.

source code of my paper "Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization"

Minimax NMF