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» Approximation algorithms for projective clustering
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IPL
1998
119views more  IPL 1998»
15 years 6 days ago
A 2.5-Factor Approximation Algorithm for the k-MST Problem
The k-MST problem requires finding that subset of at least k vertices of a given graph whose Minimum Spanning Tree has least weight amongst all subsets of at least k vertices. Th...
Sunil Arya, H. Ramesh
92
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ICALP
2005
Springer
15 years 6 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
93
Voted
CJ
2010
128views more  CJ 2010»
15 years 19 days ago
A Self-Stabilizing O(k)-Time k-Clustering Algorithm
A silent self-stabilizing asynchronous distributed algorithms is given for constructing a kdominating set, and hence a k-clustering, of a connected network of processes with uniqu...
Ajoy Kumar Datta, Lawrence L. Larmore, Priyanka Ve...
120
Voted
IAT
2009
IEEE
15 years 7 months ago
Cluster-Swap: A Distributed K-median Algorithm for Sensor Networks
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
ICML
2009
IEEE
16 years 1 months ago
Multi-view clustering via canonical correlation analysis
Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by proje...
Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu,...