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Data analysis / Data mining / Geostatistics / Machine learning / K-medians clustering / Hierarchical clustering / K-means clustering / Consensus clustering / Statistics / Multivariate statistics / Cluster analysis


Approximate Clustering without the Approximation Maria-Florina Balcan∗ Avrim Blum† Abstract
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Document Date: 2009-07-13 19:45:18

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Washington / DC / /

Company

Two Strawman Solutions / IBM / /

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United States / /

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Force Majeure / /

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Carnegie Mellon University / /

IndustryTerm

k-median solution / faster algorithms / constant-factor approximation algorithm / combinatorial algorithms / nearoptimal solution / target search algorithm / approximation algorithm / Local search heuristics / local search / icp algorithm / k-median approximation algorithm / β-approximation algorithm / above algorithm / approximation algorithms / spectral algorithm / /

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School of Computer Science / National Science Foundation / Carnegie Mellon University / Computer Science Department / /

Person

Min-Sum Clustering / Anupam Gupta / Claire Kenyon / W. Fernandez de la Vega / Marek Karpinski / Fernandez de la Vega / Yuval Rabani / R. O. Duda / /

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General / Senator / /

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C / /

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Connecticut / /

Technology

β-approximation algorithm / above algorithm / constant-factor approximation algorithm / Improved combinatorial algorithms / spectral algorithm / k-median approximation algorithm / approximation algorithm / icp algorithm / target search algorithm / k-median Algorithm / 3.2 An algorithm / Sublinear time algorithms / Case The algorithm / approximation algorithms / The algorithm / 5.2 Algorithm / machine learning / Approximation Maria-Florina Balcan∗ Avrim Blum† Abstract Approximation algorithms / same algorithm / 3.3 An Algorithm / 1 k-median Algorithm / /

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