Multiscale co-clustering for tensor data based on canonical polyadic decomposition and slice-wise factorization

DOI10.1016/j.ins.2019.06.044zbMath1453.62555OpenAlexW2952259686MaRDI QIDQ2224916

Hong Yan, Hongya Zhao, Lan Zhao, Zheng-Hong Wei

Publication date: 4 February 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2019.06.044

zbMATH Keywords

co-clusteringcanonical polyadic decompositiontensor factorizationlinear grouping

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

Co-clustering algorithms for distributional data with automated variable weighting

Uses Software

• DAVID
• MultiCluster

Cites Work

• Tensor Decompositions and Applications
• Linear grouping using orthogonal regression
• Multi-view clustering via multi-manifold regularized non-negative matrix factorization
• Matrix factorization for low-rank tensor completion using framelet prior
• A probabilistic relaxation labeling framework for reducing the noise effect in geometric biclustering of gene expression data
• Tensor Decomposition for Signal Processing and Machine Learning
• A Practical Randomized CP Tensor Decomposition
• Nonnegative Tensor Factorization, Completely Positive Tensors, and a Hierarchical Elimination Algorithm

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