Results 211 to 220 of about 54,863 (259)
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Spectral–Spatial Joint Sparse NMF for Hyperspectral Unmixing
IEEE Transactions on Geoscience and Remote Sensing, 2021The nonnegative matrix factorization (NMF) combining with spatial–spectral contextual information is an important technique for extracting endmembers and abundances of hyperspectral image (HSI).
Le Dong, Yuan Yuan, Xiaoqiang Luxs
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IEEE Transactions on Cybernetics, 2020
Non-negative matrix factorization (NMF) has become one of the most powerful methods for clustering and feature selection. However, the performance of the traditional NMF method severely degrades when the data contain noises and outliers or the manifold ...
Na Yu +4 more
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Non-negative matrix factorization (NMF) has become one of the most powerful methods for clustering and feature selection. However, the performance of the traditional NMF method severely degrades when the data contain noises and outliers or the manifold ...
Na Yu +4 more
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Semi-Supervised Graph Regularized Deep NMF With Bi-Orthogonal Constraints for Data Representation
IEEE Transactions on Neural Networks and Learning Systems, 2020Semi-supervised non-negative matrix factorization (NMF) exploits the strengths of NMF in effectively learning local information contained in data and is also able to achieve effective learning when only a small fraction of data is labeled.
Yang Meng +5 more
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Statistical Analysis of Microarray Data Clustering using NMF, Spectral Clustering, Kmeans, and GMM
IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2020In unsupervised learning literature, the study of clustering using microarray gene expression datasets has been extensively conducted with nonnegative matrix factorization (NMF), spectral clustering, kmeans, and gaussian mixture model (GMM)are some of ...
Andri Mirzal
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Experimental explorations on short text topic mining between LDA and NMF based Schemes
Knowledge-Based Systems, 2019Learning topics from short texts has become a critical and fundamental task for understanding the widely-spread streaming social messages, e.g., tweets, snippets and questions/answers.
Yong Chen +4 more
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Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014
Non-negative matrix factorization (NMF) is a well known method for obtaining low rank approximations of data sets, which can then be used for efficient indexing, classification, and retrieval. The non-negativity constraints enable probabilistic interpretation of the results and discovery of generative models.
Xilun Chen, K. Selçuk Candan
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Non-negative matrix factorization (NMF) is a well known method for obtaining low rank approximations of data sets, which can then be used for efficient indexing, classification, and retrieval. The non-negativity constraints enable probabilistic interpretation of the results and discovery of generative models.
Xilun Chen, K. Selçuk Candan
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IEEE journal of biomedical and health informatics, 2020
Non-negative Matrix Factorization (NMF) is a dimensionality reduction approach for learning a parts-based and linear representation of non-negative data. It has attracted more attention because of that.
Cui-Na Jiao +4 more
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Non-negative Matrix Factorization (NMF) is a dimensionality reduction approach for learning a parts-based and linear representation of non-negative data. It has attracted more attention because of that.
Cui-Na Jiao +4 more
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Subspace Clustering Constrained Sparse NMF for Hyperspectral Unmixing
IEEE Transactions on Geoscience and Remote Sensing, 2020As one of the most important information of hyperspectral images (HSI), spatial information is usually simulated with the similarity among pixels to enhance the unmixing performance of nonnegative matrix factorization (NMF).
Xiaoqiang Lu, Le Dong, Yuan Yuan
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Topic Modeling Coherence: A Comparative Study between LDA and NMF Models using COVID’19 Corpus
, 2020Topic modeling is a method for finding abstract topics in a large collection of documents With it, it is possible to discover the mixture of hidden or “latent” topics that varies from document to document in a given corpus As an unsupervised machine ...
S. Mifrah, E. Benlahmar
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Kinetic study on the slow pyrolysis of nonmetal fraction of waste printed circuit boards (NMF-WPCBs)
Waste Management Research, 2020In this study, the pyrolysis behaviour of nonmetal fraction of waste printed circuit boards (NMF-WPCBs) was studied based on five model-free methods and distributed activation energy model (DAEM).
Z. Yao +6 more
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