Results 11 to 20 of about 13,867 (163)
Hypergraph based semi-supervised symmetric nonnegative matrix factorization for image clustering
Pattern Recognition, 2023 Semi-supervised symmetric nonnegative matrix factorization (SNMF) has been shown to be a significant method for both linear and nonlinear data clustering applications. Nevertheless, existing SNMF-based methods only adopt a simple graph to construct the similarity matrix, and cannot fully use the limited supervised information for the construction of ...
Jingxing Yin +4 more
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WSNMF: Weighted Symmetric Nonnegative Matrix Factorization for attributed graph clustering
NeurocomputingIn recent times, Symmetric Nonnegative Matrix Factorization (SNMF), a derivative of Nonnegative Matrix Factorization (NMF), has surfaced as a promising technique for graph clustering. Nevertheless, when applied to attributed graph clustering, it confronts notable challenges.
Kamal Berahmand +4 more
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Block Sparse Symmetric Nonnegative Matrix Factorization Based on Constrained Graph Regularization [PDF]
Jisuanji kexue, 2023 The existing algorithms based on symmetric nonnegative matrix factorization(SymNMF) are mostly rely on initial data to construct affinity matrices,and neglect the limited pairwise constraints,so these methods are unable to effectively distinguish similar
LIU Wei, DENG Xiuqin, LIU Dongdong, LIU Yulan
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Off-diagonal symmetric nonnegative matrix factorization [PDF]
Numerical Algorithms, 2021 Symmetric nonnegative matrix factorization (symNMF) is a variant of nonnegative matrix factorization (NMF) that allows to handle symmetric input matrices and has been shown to be particularly well suited for clustering tasks. In this paper, we present a new model, dubbed off-diagonal symNMF (ODsymNMF), that does not take into account the diagonal ...
François Moutier +2 more
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SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association. [PDF]
RNA Biol, 2020 Zhao Y, Chen X, Yin J, Qu J.
europepmc +2 more sources
Exponential Lower Bounds for Polytopes in Combinatorial Optimization [PDF]
, 2015 We solve a 20-year old problem posed by Yannakakis and prove that there exists no polynomial-size linear program (LP) whose associated polytope projects to the traveling salesman polytope, even if the LP is not required to be symmetric.
de Wolf, Ronald +4 more
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Frontiers in Molecular Biosciences, 2021 A network is an efficient tool to organize complicated data. The Laplacian graph has attracted more and more attention for its good properties and has been applied to many tasks including clustering, feature selection, and so on.
Junmin Zhao, Yuanyuan Ma, Lifang Liu
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Robust Community Detection in Graphs
IEEE Access, 2021 Community detection in network-type data provides a powerful tool in analyzing and understanding real-world systems. In fact, community detection approaches aim to reduce the network’s dimensionality and partition it into a set of disjoint ...
Esraa M. Al-Sharoa +2 more
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Symmetric Nonnegative Matrix Factorization Based on Box-Constrained Half-Quadratic Optimization
IEEE Access, 2020 Nonnegative Matrix Factorization (NMF) based on half-quadratic (HQ) functions was proven effective and robust when dealing with data contaminated by continuous occlusion according to the half-quadratic optimization theory.
Bo-Wei Chen
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Adaptive computation of the Symmetric Nonnegative Matrix Factorization (SymNMF)
SeMA Journal, 2020 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 +3 more
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