# K-medians clustering

## Papers overview

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2016

2016

- 2016

Data mining responsibilities show the broad features of the data in the database and also examine the current data in order toâ€¦Â (More)

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2015

2015

- IEEE International Conference on Acousticsâ€¦
- 2015

Principal Component Analysis (PCA) is one of the most widely used tools for the representation of high-dimensional data. Manyâ€¦Â (More)

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2015

2015

- Seventh International Conference on Advancedâ€¦
- 2015

Brain storm optimization (BSO) algorithm is a novel swarm intelligence algorithm inspired by human beings' brainstorming processâ€¦Â (More)

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2014

2014

- Theory of Computing Systems
- 2014

The focus of our work is introducing and constructing probabilistic coresets. A probabilistic coreset can contain probabilisticâ€¦Â (More)

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2004

2004

- Theor. Comput. Sci.
- 2004

In the incremental versions of Facility Location and k-Median, the demand points arrive one at a time and the algorithm maintainsâ€¦Â (More)

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Highly Cited

2003

Highly Cited

2003

- PODS
- 2003

The sliding window model is useful for discounting stale data in data stream applications. In this model, data elements arriveâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- J. Comput. Syst. Sci.
- 2002

We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of theâ€¦Â (More)

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2000

2000

- SSPR/SPR
- 2000

Clustering in Metric Spaces can be conveniently performed by the so called k-medians method. It consists of a variant of theâ€¦Â (More)

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Highly Cited

1999

Highly Cited

1999

- STOC
- 1999

1 Introduction We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problemâ€¦Â (More)

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1998

Highly Cited

1998

- STOC
- 1998

In the k-median problem we are given a set S of n points in a metric space and a positive integer k. We desire to locate kâ€¦Â (More)

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