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tuhma documents
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Stephen J. Verzi et al- Universal Approximation, With Fuzzy ART and. Fuzzy ARTMAP
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Lachlan L.H. Andrew- Improving the Robustness of Winner-Take- All Cellular Neural Networks
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J.-H.Wang and J.-D.Rau- VQ-agglomeration: a novel approach to clustering
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Toshihiko Ogura, Kenji Iwasaki and Chikara Sato- Topology representing network enables highly accurate classification of protein images taken by cryo electron-microscope without masking
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Frank-Michael Schleif, Andrej Gisbrecht and Barbara Hammer- Accelerating Kernel Neural Gas
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Banchar Arnonkijpanich, Barbara Hammer and Alexander Hasenfuss- Local Matrix Adaptation in Topographic Neural Maps
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Kai Labusch, Erhardt Barth and Thomas Martinetz- Learning Data Representations with Sparse Coding Neural Gas
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Chang Liang et al- Scaling up Kernel Grower Clustering Method for Large Data Sets via Core-sets
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F.-M. Schleif, B. Hammer and T. Villmann- Margin based Active Learning for LVQ Networks
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Barbara Hammer and Alexander Hasenfuss- Topographic Mapping of Large Dissimilarity Data Sets
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Frank-Michael Schleif- Sparse Kernelized Vector Quantization with Local Dependencies
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Frank-Michael Schleif et al- Generalized derivative based kernelized Learning Vector Quantization
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Frank-Michael Schleif, Matthias Ongyerth and Thomas Villmann- Sparse coding Neural Gas for analysis of Nuclear Magnetic Resonance Spectroscopy
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Kai Labusch, Erhardt Barth and Thomas Martinetz- Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas
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Kai Labusch, Erhardt Barth and Thomas Martinetz- Sparse Coding Neural Gas: Learning of Overcomplete Data Representations
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T. Villmann et al- Fuzzy Labeled Neural Gas for Fuzzy Classification
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Jim Holmström- Growing Neural Gas: Experiments with GNG, GNG with Utility and Supervised GNG
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Václav Hlavác- Linear classifiers, a perceptron family
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