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On clusterings-good, bad and spectral

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3 Author(s)
Kannan, R. ; Dept. of Comput. Sci., Yale Univ., New Haven, CT, USA ; Vempala, S. ; Veta, A.

We propose a new measure for assessing the quality of a clustering. A simple heuristic is shown to give worst-case guarantees under the new measure. Then we present two results regarding the quality of the clustering found by a popular spectral algorithm. One proffers worst case guarantees whilst the other shows that if there exists a “good” clustering then the spectral algorithm will find one close to it

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Foundations of Computer Science, 2000. Proceedings. 41st Annual Symposium on

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