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K-medians clustering

Known as: K-median problem, K-medians 
In statistics and data mining, k-medians clustering is a cluster analysis algorithm. It is a variation of k-means clustering where instead of… Expand
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Papers overview

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Highly Cited
2010
Highly Cited
2010
We study the problem of minimizing the diameter of a graph by adding k shortcut edges, for speeding up communication in an… Expand
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2009
2009
Consider the following problem: given a metric space, some of whose points are “clients,” select a set of at most k facility… Expand
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Highly Cited
2005
Highly Cited
2005
In this paper we give a constant factor approximation algorithm for the capacitated k-median problem. Our algorithm produces a… Expand
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Highly Cited
2003
Highly Cited
2003
The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arrive… Expand
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Highly Cited
2002
Highly Cited
2002
We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the… Expand
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Highly Cited
2002
Highly Cited
2002
We present a simple and natural greedy algorithm for the metric uncapacitated facility location problem achieving an… Expand
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Highly Cited
2002
Highly Cited
2002
We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen… Expand
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Highly Cited
2000
Highly Cited
2000
The paper gives approximation algorithms for the k-medians and facility-location problems (both NP-hard). For k-medians, the… Expand
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Highly Cited
1999
Highly Cited
1999
1 Introduction We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem… Expand
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Highly Cited
1999
Highly Cited
1999
  • K. Jain, V. Vazirani
  • 40th Annual Symposium on Foundations of Computer…
  • 1999
  • Corpus ID: 17518409
We present approximation algorithms for the metric uncapacitated facility location problem and the metric k-median problem… Expand
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