Nonnegative tensor factorization as an alternative Csiszar-Tusnady procedure: algorithms, convergence, probabilistic interpretations and novel probabilistic tensor latent variable analysis algorithms

DOI10.1007/s10618-010-0196-4zbMath1235.65041OpenAlexW2129455341MaRDI QIDQ408627

Maria Petrou, Stefanos P. Zafeiriou

Publication date: 11 April 2012

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-010-0196-4

zbMATH Keywords

Kullback-Leibler divergencenonnegative matrix factorizationnonnegative tensor factorizationprobabilistic latent semantic analysis

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Learning and adaptive systems in artificial intelligence (68T05) Convergence of probability measures (60B10)

Related Items (3)

Newton-based optimization for Kullback–Leibler nonnegative tensor factorizations ⋮ Higher rank support tensor machines for visual recognition ⋮ Algorithmic and optimization aspects of Brascamp-Lieb inequalities, via operator scaling

Uses Software

• FERET
• XM2VTSDB

Cites Work

• Unnamed Item
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• Algorithms for Sparse Nonnegative Tucker Decompositions
• Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization
• Supervised and Semi-supervised Separation of Sounds from Single-Channel Mixtures
• Algorithms for Nonnegative Tensor Factorization
• A Multilinear Singular Value Decomposition
• Learning the parts of objects by non-negative matrix factorization
• Projected Gradient Methods for Nonnegative Matrix Factorization

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