196,097 research outputs found
Recursive self-organizing network models
No full textHammer B, Micheli A, Sperduti A, Strickert M. Recursive self-organizing network models. Neural Networks. 2004;17(8-9):1061-1085
A general framework for unsupervised processing of structured data
No full textHammer B, Micheli A, Sperduti A, Strickert M. A general framework for unsupervised processing of structured data. Neurocomputing. 2004;57:3-35
Neural Gas for Sequences
No full textStrickert M, Hammer B. Neural Gas for Sequences. In: WSOM'03. 2003: 53-57
Merge SOM for temporal data
No full textStrickert M, Hammer B. Merge SOM for temporal data. Neurocomputing. 2005;64:39-71
Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments
No full textStrickert M, Schleif F-M. Supervised Attribute Relevance Determination for Protein Identification in Stress Experiments. In: Proc. of MLSB 2007. 2007: 81-86
Gradients of Pearson Correlation for Analysis of Biomedical Data
No full textStrickert M, Schleif F-M, Seiffert U. Gradients of Pearson Correlation for Analysis of Biomedical Data. In: Proc. of ASAI 2007. 2007: 139-150
On the generalization ability of GRLVQ networks
No full textHammer B, Strickert M, Villmann T. On the generalization ability of GRLVQ networks. Neural Processing Letters. 2005;21(2):109-120
Unsupervised recursive sequences processing
No full textStrickert M, Hammer B, Blohm S. Unsupervised recursive sequences processing. Neurocomputing. 2005;63:69-97
Self-organizing context learning
No full textStrickert M, Hammer B. Self-organizing context learning. In: Verleysen M, ed. European Symposium on Artificial Neural Networks. D-side publications; 2004: 39-44
Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data
No full textStrickert M, Schleif F-M, Seiffert U. Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data. Ibero-American Journal of Artificial Intelligence. 2008;37(12):37-44
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