Results 121 to 130 of about 23,929 (166)

Glycan mixture analysis by kernel component composition for matrix factorization. [PDF]

Anal Bioanal Chem
Hong P, Xia C, Tang Y, Wei J, Lin C.
europepmc   +1 more source

A Novel Drug-Disease Association Prediction Method Based on Deep Non-Negative Matrix Factorization with Local Graph Feature. [PDF]

Interdiscip Sci
Yang M, Yang B, Chen J, Tang X, Duan G.
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Bayesian multi-study non-negative matrix factorization for mutational signatures. [PDF]

Genome Biol
Grabski IN, Trippa L, Parmigiani G.
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Robust self supervised symmetric nonnegative matrix factorization to the graph clustering. [PDF]

Sci Rep
Ru Y, Gruninger M, Dou Y.
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GCNMF-SDA: predicting snoRNA-disease associations based on graph convolution and non-negative matrix factorization. [PDF]

Brief Bioinform
Zhang Y, Jin X, Zhang X.
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ARTdeConv: adaptive regularized tri-factor non-negative matrix factorization for cell type deconvolution. [PDF]

NAR Genom Bioinform
Liu T, Liu C, Li Q, Zheng X, Zou F.
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Factor-Bounded Nonnegative Matrix Factorization

ACM Transactions on Knowledge Discovery from Data, 2021
Nonnegative Matrix Factorization (NMF) is broadly used to determine class membership in a variety of clustering applications. From movie recommendations and image clustering to visual feature extractions, NMF has applications to solve a large number of knowledge discovery and data mining problems.
Kai Liu 0018, Xiangyu Li, Zhihui Zhu, Lodewijk Brand, Hua Wang 0007   +4 more
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Ternary Matrix Factorization

2014 IEEE International Conference on Data Mining, 2014
Can we learn from the unknown? Logical data sets of the ternary kind are often found in information systems. They contain unknown as well as true/false values. An unknown value may represent a missing entry (lost or indeterminable) or something with meaning, like a 'Don't Know' response in a questionnaire. In this paper we introduce an effectively- and
Samuel Maurus, Claudia Plant
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