A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering-Reference-Cited by-同舟云学术

A Framework for Statistical Clustering with a Constant Time Approximation Algorithms for K-Median Clustering

Published:2004 Issue: Volume: Page:415-426
ISSN:0302-9743
Container-title:Learning Theory
language:
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Author:

Ben-David Shai

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-27819-1_29.pdf

Reference8 articles.

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3. Buhmann, J.: Empirical Risk Approximation: An Induction Principle for Unsupervised Learning . Technical Report IAI-TR-98-3, Institut for Informatik III, Universitat Bonn (1998)

4. Meyerson, A., O’Callaghan, L., Plotkin, S.: A k-median Algorithm with Running Time Independent of Data Size. Journal of Machine Learning, Special Issue on Theoretical Advances in Data Clustering, MLJ (2004)

5. Mishra, N., Oblinger, D., Pitt, L.: Sublinear Time Approximate Clustering. In: Proceedings of Syposium on Discrete Algorithms, SODA, pp. 439–447 (2001)

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