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» Approximation Algorithms for Clustering Problems
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CJ
2010
128views more  CJ 2010»
14 years 9 months 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...
COLT
2003
Springer
15 years 2 months ago
On Finding Large Conjunctive Clusters
We propose a new formulation of the clustering problem that differs from previous work in several aspects. First, the goal is to explicitly output a collection of simple and meani...
Nina Mishra, Dana Ron, Ram Swaminathan
NIPS
2008
14 years 11 months ago
Clustering via LP-based Stabilities
A novel center-based clustering algorithm is proposed in this paper. We first formulate clustering as an NP-hard linear integer program and we then use linear programming and the ...
Nikos Komodakis, Nikos Paragios, Georgios Tziritas
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
14 years 7 months ago
Maximum Margin Clustering with Multivariate Loss Function
This paper presents a simple but powerful extension of the maximum margin clustering (MMC) algorithm that optimizes multivariate performance measure specifically defined for clust...
Bin Zhao, James Tin-Yau Kwok, Changshui Zhang
RECOMB
2008
Springer
15 years 9 months ago
Computation of Median Gene Clusters
Whole genome comparison based on gene order has become a popular approach in comparative genomics. An important task in this field is the detection of gene clusters, i.e. sets of g...
Sebastian Böcker, Katharina Jahn, Julia Mixta...