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Nonnegative Matrix Factorization (NMF) Based Supervised Feature Selection and Adaptation
2008We proposed a novel algorithm of supervised feature selection and adaptation for enhancing the classification accuracy of unsupervised Nonnegative Matrix Factorization (NMF) feature extraction algorithm. At first the algorithm extracts feature vectors for a given high dimensional data then reduce the feature dimension using mutual information based ...
Barman, Paresh Chandra, Lee, Soo-Young
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The Journal of Supercomputing, 2018
Nonnegative matrix factorization (NMF) has become a powerful model for community discovery in complex networks. Existing NMF-based methods for community discovery often factorize the corresponding adjacent matrix of complex networks to obtain its community indicator matrix.
Chaobo He +5 more
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Nonnegative matrix factorization (NMF) has become a powerful model for community discovery in complex networks. Existing NMF-based methods for community discovery often factorize the corresponding adjacent matrix of complex networks to obtain its community indicator matrix.
Chaobo He +5 more
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2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), 2017
With the ever growing collection of large volumes of scientific data, development of interpretable machine learning tools to analyze such data is becoming more important. However, robust, interpretable machine learning tools are lacking, threatening extraction of scientific insight and discovery.
Shashanka Ubaru +2 more
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With the ever growing collection of large volumes of scientific data, development of interpretable machine learning tools to analyze such data is becoming more important. However, robust, interpretable machine learning tools are lacking, threatening extraction of scientific insight and discovery.
Shashanka Ubaru +2 more
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2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019
In this paper, the problem of electrodes shift is studied in low-density surface electromyographic (sEMG) based prosthetic control with the proposed Sliding Window Nonnegative Matrix Factorization (SW-NMF) algorithm. By artificially switching the electrode positions clockwise for π/8, the 8 channel sEMG signals of 10 gestures were recorded before and ...
Zhien Xian +4 more
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In this paper, the problem of electrodes shift is studied in low-density surface electromyographic (sEMG) based prosthetic control with the proposed Sliding Window Nonnegative Matrix Factorization (SW-NMF) algorithm. By artificially switching the electrode positions clockwise for π/8, the 8 channel sEMG signals of 10 gestures were recorded before and ...
Zhien Xian +4 more
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Adaptive computation of the Symmetric Nonnegative Matrix Factorization (NMF)
2018Nonnegative Matrix Factorization (NMF), first proposed in 1994 for data analysis, has received successively much attention in a great variety of contexts such as data mining, text clustering, computer vision, bioinformatics, etc. In this paper the case of a symmetric matrix is considered and the symmetric nonnegative matrix factorization (SymNMF) is ...
P. Favati (1) +3 more
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SAR Images Clustering Based on Modified Nonlinear Orthogonal Nonnegative Matrix Factorization (NMF)
2023 31st International Conference on Electrical Engineering (ICEE), 2023Mahdi Jowkar Dehouei +2 more
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Robust Manifold Nonnegative Matrix Factorization
ACM Transactions on Knowledge Discovery From Data, 2014Feiping Nie, Heng Huang, Chris Ding
exaly
SVD based initialization: A head start for nonnegative matrix factorization
Pattern Recognition, 2008Efstratios Gallopoulos
exaly
Nonnegative Matrix Factorization: A Comprehensive Review
IEEE Transactions on Knowledge and Data Engineering, 2013Yu-Jin Zhang, Yu-Xiong Wang
exaly

