Coreset

In computational geometry, a coreset is a small set of points that approximates the shape of a larger point set, in the sense that applying some… (More)
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Papers overview

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2017
2017
We present a new Frank-Wolfe (FW) type algorithm that is applicable to minimization problems with a nonsmooth convex objective… (More)
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Highly Cited
2013
Highly Cited
2013
We develop and analyze a method to reduce the size of a very large set of data points in a high dimensional Euclidean space Rd to… (More)
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Highly Cited
2011
Highly Cited
2011
How can we train a statistical mixture model on a massive data set? In this paper, we show how to construct coresets for mixtures… (More)
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Highly Cited
2009
Highly Cited
2009
We present new approximation algorithms for the k-median and k-means clustering problems. To this end, we obtain small coresets… (More)
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Highly Cited
2008
Highly Cited
2008
The ℓ<sub><i>p</i></sub> <i>regression problem</i> takes as input a matrix <i>A</i> ∈ ℝ<sup><i>n</i></sup>, a vector <i>b</i… (More)
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Highly Cited
2007
Highly Cited
2007
Given a point set P ⊆ R<sup>d</sup> the k-means clustering problem is to find a set C=(c<sub>1</sub>,...,c<sub>k</sub>) of k… (More)
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Highly Cited
2005
Highly Cited
2005
The paradigm of coresets has recently emerged as a powerful tool for efficiently approximating various extent measures of a point… (More)
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Highly Cited
2005
Highly Cited
2005
A dynamic geometric data stream consists of a sequence of <i>m</i> insert/delete operations of points from the discrete space 1… (More)
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Highly Cited
2004
Highly Cited
2004
In this paper, we show the existence of small coresets for the problems of computing k-median and k-means clustering for points… (More)
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Highly Cited
2003
Highly Cited
2003
In this paper, we show the existence of small coresets for the problems of computing k-median and kmeans clustering for points in… (More)
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