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Active Topographic Mapping of Proximities
Citation key Hasenjaeger1999b0
Author Hasenjäger, M. and Ritter, H. and Obermayer, K.
Title of Book 9th International Conference on Artificial Neural Networks - ICANN99
Pages 952 – 957
Year 1999
ISBN 0-85296-721-7
ISSN 0537-9989
DOI 10.1049/cp:19991235
Publisher IEEE
Abstract We deal with the question of how to reduce the computational costs of obtaining and clustering dissimilarity data. We show that for pairwise clustering, a large portion of the dissimilarity data can be neglected without incurring a serious deterioration of the clustring solution. This fact can be exploited by selecting the dissimilarity values that are supposed to be most relevant in a well-directed manner. We present an algorithm for active data selection for topographic pairwise clustering that aims at maximizing the expected reduction in the clustering cost function and propose a computationally more efficient approximation to this algorithm, that yields satisfactory results in cases where the topography is imposed only weakly.
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