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• M. Hasenjäger, H. Ritter, and K. Obermayer. Active Topographic Mapping of Proximities. . In 9th International Conference on Artificial Neural Networks - ICANN99, pages 952-957, 1999.
  (FTP Gzipped PostScript, 6 pages, 67 kb)

  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.