Results 151 to 160 of about 1,628,183 (185)

Scalable cell-specific coexpression networks for granular regulatory pattern discovery with NeighbourNet. [PDF]

Genome Res
Deng Y, Mao J, Choi J, Lê Cao KA.
europepmc   +1 more source

Unbiased clustering of acute-on-chronic liver failure patients using machine learning in a real-world ICU cohort. [PDF]

Nat Commun
Zhang M, Ji F, Zu J, He Y, Chen T, Liu Y, Trivedi HD, Yang JD, Sundaram V, Wang Y, Sun X, Cao Z, Wu CY, Yeo YH, Jalan R.   +14 more
europepmc   +1 more source

Multiomic and functional validation of ACSL3, a regulator of fatty acid metabolism, as a lymph node metastasis-associated gene in lung adenocarcinoma. [PDF]

Respir Res
Liang Y, Liang L, Du M, Lei Y, Gao Y, Li S.   +5 more
europepmc   +1 more source

Spatiospectral signatures of stomach-brain synchrony

Berther T, Saltafossi M, Fehring J, Rebollo I, Kluger DS.   +4 more
europepmc   +1 more source

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Search Results Clustering Using Nonnegative Matrix Factorization (NMF)

2009 International Conference on Advances in Social Network Analysis and Mining, 2009
There are many search engines in the web and when asked, they return a long list of search results, ranked by their relevancies to the given query. Web users have to go through the list and examine the titles and (short) snippets sequentially to identify their required results. In this paper we present how usage of Nonnegative Matrix Factorization (NMF)
Václav Snasel
exaly   +6 more sources

Nonnegative Matrix Factorization (NMF) Based Supervised Feature Selection and Adaptation

Lecture Notes in Computer Science, 2008
We 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 ...
Soo-Young Lee
exaly   +4 more sources

Adaptive computation of the Symmetric Nonnegative Matrix Factorization (NMF)

, 2018
Nonnegative 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), G. Lotti (2), O. Menchi (3), F. Romani (3)   +3 more
openaire   +2 more sources

Secure and Verifiable Outsourcing of Large-Scale Nonnegative Matrix Factorization (NMF)

IEEE Transactions on Services Computing, 2021
Nowadays, cloud computing platforms are becoming increasingly prevalent and readily available, providing alternative and economic services for resource-constrained clients to perform large-scale computations. This work addresses the problem of secure outsourcing of large-scale nonnegative matrix factorization (NMF) to a cloud in a way that the client ...
Jia Duan, Jiantao Zhou 0001, Yuanman Li
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Source apportionment of atmospheric particle number concentrations with wide size range by nonnegative matrix factorization (NMF)

Environmental Pollution, 2021
Quantifying the sources of atmospheric particles is essential to air quality control but remains challenging, especially for the source apportionment of particles based on number concentration with wide size range. Here, particle number concentrations (PNC) with size range 19-20,000 nm involving four modes Nucleation, Aitken, Accumulation, and Coarse ...
Chun-Sheng Liang, Dingli Yue, Hao Wu, Jin-Sen Shi, Ke-Bin He   +4 more
openaire   +2 more sources