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This paper describe a suite of data mining tools that cover clustering, information retrieval and the mapping of high dimensional data to low dimensions for visualization. Preliminary applications are given to particle physics, bioinformatics and medical informatics. The data vary in dimension from low (2-20), high (Thousands) to undefined (Sequences with dissimilarities but not vectors defined). The authors use deterministic annealing to provide more robust algorithms that are relatively insensitive to local minima.
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