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» Approximation Algorithms for Clustering Problems
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AAAI
2006
15 years 8 months ago
Identifying and Generating Easy Sets of Constraints for Clustering
Clustering under constraints is a recent innovation in the artificial intelligence community that has yielded significant practical benefit. However, recent work has shown that fo...
Ian Davidson, S. S. Ravi
SODA
2012
ACM
200views Algorithms» more  SODA 2012»
13 years 9 months ago
The shifting sands algorithm
We resolve the problem of small-space approximate selection in random-order streams. Specifically, we present an algorithm that reads the n elements of a set in random order and ...
Andrew McGregor, Paul Valiant
IPPS
2002
IEEE
15 years 11 months ago
Distribution Sweeping on Clustered Machines with Hierarchical Memories
This paper investigates the design of parallel algorithmic strategies that address the efficient use of both, memory hierarchies within each processor and a multilevel clustered ...
Frank K. H. A. Dehne, Stefano Mardegan, Andrea Pie...
STACS
2009
Springer
16 years 1 months ago
On Approximating Multi-Criteria TSP
Abstract. We present approximation algorithms for almost all variants of the multicriteria traveling salesman problem (TSP), whose performances are independent of the number k of c...
Bodo Manthey
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 8 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon