Cichocki, A., Zdunek, R.: Multilayer nonnegative matrix factorization using projected gradient approaches. Int. J. Neural Syst. 17 (6), 431–446 (2007)Cichocki and Zdunck (2007) Multi-layer nonnegative matrix factorization using projected gradient approaches. International Journal of Neural System...
For linear models, multilayer nonnegative matrix factorization (MLNMF) based algorithms are quite popular to estimate fractional abundances from the hyperspectral data [25]. These methods process the unmixing problem as a layer-by-layer decomposition process [26]. The MLNMF-based methods ultimately ...
Speech enhancement based on nonnegative matrix factorization in constant-q frequency domain Appl. Acoust., 174 (2021), pp. 481-496 View in ScopusGoogle Scholar [26] Md. Shah Fahad, Ashish Ranjan, Jainath Yadav, Akshay Deepak A survey of speech emotion recognition in natural environment Digit....
Ortiz-Bouza et al.42 proposed a multiple orthogonal nonnegative matrix TriFactorization method to achieve the detection of cross-layer communities in multilayer networks as well as unique communities on a single layer; in 2023, Roozbahani et al.43 designed a multi-relational directed network...
Symmetric nonnegative matrix factorization for graph clustering. In: Proceedings of 2012 SIAM international conference on data mining; 2012. p. 106–17. SIAM. Zitnik M, Leskovec J. Predicting multicellular function through multi-layer tissue networks. Bioinformatics. 2017;33(14):190–8. Article ...
with TP = true positive, FP = false positive, FN = false negative and TN = true negative. Besides, Rand Index is also a popular measure, which represents the percentage of TP and TN decisions assigns that are correct (i.e. accuracy), defined as ...
Nonnegative matrix factorizationBackpropagationWe introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data. Datasets with hierarchical structure arise in a wide variety of fields, such as document classification, image processing, and...
doi:10.1049/el:20070599A correction to the article "Multilayer nonnegative matrix factorization" that was published in the March 29, 2007 issue is presented.CichockiLaboratoryA.LaboratoryZdunekLaboratoryR.LaboratoryEBSCO_bspElectronics Letters
Nonnegative matrix factorization (NMF) is a widely used method of endmember extraction due to its effectiveness and convenience. While most NMF-based methods have single-layer structures, which may have difficulties in effectively learning the structures of highly mixed and complex data. On the ...
Nonnegative matrix factorization (NMF) has been widely used in HU due to its simplicity and effectiveness. Many extensions of NMF have been also developed since traditional NMF has a large solution space. On the other hand, the multilayer structure has shown great advantages in learning data ...