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Approximation Algorithms for Some Clustering and Classification Problems

  • Eva Tardos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1741)

Abstract

Clustering and classification problems arise in a wide range of application settings from clustering documents, placing centers in net- works, to image processing, biometric analysis, language modeling and the categorization of hypertext documents.

The applications mentioned above give rise to a number of related al- gorithms problems, each of which are NP-complete. Approximation al- gorithms provide a framework to develop algorithms for such problems that have provable performance guarantees. In this talk we shall survey some of the general techniques, and recent developments in approxima- tion algorithms for these problems.

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Eva Tardos
    • 1
  1. 1.Department of Computer ScienceCornell UniversityIthacaUSA

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