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Information Processing and Management: an International Journal
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UIST '94 Proceedings of the 7th annual ACM symposium on User interface software and technology
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Neural Computation
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IEEE Transactions on Visualization and Computer Graphics
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ECML '98 Proceedings of the 10th European Conference on Machine Learning
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ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
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Neural Processing Letters
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Neural Networks - 2004 Special issue: New developments in self-organizing systems
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IEEE Computer Graphics and Applications
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IEEE Transactions on Neural Networks
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IEEE Transactions on Neural Networks
Classification Visualization across Mapping on a Sphere
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
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IEEE Transactions on Neural Networks
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Pattern Recognition
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ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
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Mathematical and Computer Modelling: An International Journal
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Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies
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Intelligent Data Analysis
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We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that allows for incremental training with an automated adaptation of lattice size to achieve a prescribed quantization error and (ii) an approximate best match search that utilizes the special structure of the hyperbolic lattice to achieve a tremendous speed-up for large map sizes. Using the MNIST and the Reuters-21578 database as benchmark datasets, we show that the H2SOM yields a highly efficient visualization algorithm that combines the virtues of the SOM with extremely rapid training and low quantization and classification errors.