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» Approximation Algorithms for Clustering Problems
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ICML
2007
IEEE
16 years 5 months ago
Online discovery of similarity mappings
We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated ...
Alexander Rakhlin, Jacob Abernethy, Peter L. Bartl...
SDM
2007
SIAM
74views Data Mining» more  SDM 2007»
15 years 6 months ago
HACS: Heuristic Algorithm for Clustering Subsets
The term consideration set is used in marketing to refer to the set of items a customer thought about purchasing before making a choice. While consideration sets are not directly ...
Ding Yuan, W. Nick Street
ESA
2006
Springer
103views Algorithms» more  ESA 2006»
15 years 8 months ago
Greedy in Approximation Algorithms
The objective of this paper is to characterize classes of problems for which a greedy algorithm finds solutions provably close to optimum. To that end, we introduce the notion of k...
Julián Mestre
ESANN
2004
15 years 6 months ago
Clustering functional data with the SOM algorithm
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Fabrice Rossi, Brieuc Conan-Guez, Aïcha El Go...
IJKESDP
2010
149views more  IJKESDP 2010»
15 years 3 months ago
An approximate solution method based on tabu search for k-minimum spanning tree problems
—This paper considers k-minimum spanning tree problems. An existing solution algorithm based on tabu search, which was proposed by Katagiri et al., includes an iterative solving ...
Hideki Katagiri, Tomohiro Hayashida, Ichiro Nishiz...