Self-organizing maps and clustering methods for matrix data

DOI10.1016/j.neunet.2004.06.012zbMath1079.68598OpenAlexW2075073685WikidataQ30976795 ScholiaQ30976795MaRDI QIDQ2485243

Klaus Obermayer, Sambu Seo

Publication date: 3 August 2005

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2004.06.012

zbMATH Keywords

Self-organizing mapsCo-occurrence dataDeterministic annealingGrowing networkInformation bottleneckMatrix dataMaximum entropy methodsPairwise clusteringRate distortion theory

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (4)

Topographic Mapping of Large Dissimilarity Data Sets ⋮ Batch and median neural gas ⋮ Fast algorithm and implementation of dissimilarity self-organizing maps ⋮ Granular self-organizing map (grSOM) for structure identification

Uses Software

• GTM

Cites Work

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• Enlarging the region of convergence of Newton's method for constrained optimization
• Self-organized formation of topologically correct feature maps
• Analysis of a simple self-organizing process
• Self-organizing maps: Ordering, convergence properties and energy functions
• Theoretical aspects of the SOM algorithm
• Modern multidimensional scaling: theory and applications
• Clustering Based on Conditional Distributions in an Auxiliary Space
• Information Theory and Statistical Mechanics
• Vector quantization by deterministic annealing
• A Bayesian Analysis of Self-Organizing Maps
• Self-organizing maps.

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