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135
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STOC
2003
ACM
140views Algorithms» more  STOC 2003»
16 years 3 months ago
Approximation schemes for clustering problems
We present a general approach for designing approximation algorithms for a fundamental class of geometric clustering problems in arbitrary dimensions. More specifically, our appro...
Wenceslas Fernandez de la Vega, Marek Karpinski, C...
COCOON
2010
Springer
15 years 8 months ago
Clustering with or without the Approximation
We study algorithms for clustering data that were recently proposed by Balcan, Blum and Gupta in SODA’09 [4] and that have already given rise to two follow-up papers. The input f...
Frans Schalekamp, Michael Yu, Anke van Zuylen
133
Voted
ISAAC
2004
Springer
121views Algorithms» more  ISAAC 2004»
15 years 8 months ago
Approximate Distance Oracles for Graphs with Dense Clusters
Let G be a graph containing N disjoint t-spanners that are inter-connected with M edges. We present an algorithm that constructs a data structure of size O(M2 + n log n) that answ...
Mattias Andersson, Joachim Gudmundsson, Christos L...
113
Voted
ICML
2006
IEEE
16 years 4 months ago
Clustering documents with an exponential-family approximation of the Dirichlet compound multinomial distribution
The Dirichlet compound multinomial (DCM) distribution, also called the multivariate Polya distribution, is a model for text documents that takes into account burstiness: the fact ...
Charles Elkan
ICALP
2005
Springer
15 years 8 months ago
Linear Time Algorithms for Clustering Problems in Any Dimensions
Abstract. We generalize the k-means algorithm presented by the authors [14] and show that the resulting algorithm can solve a larger class of clustering problems that satisfy certa...
Amit Kumar, Yogish Sabharwal, Sandeep Sen