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» Approximation Algorithms for Clustering Problems
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112
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CJ
2010
128views more  CJ 2010»
15 years 2 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...
125
Voted
COLT
2003
Springer
15 years 7 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
104
Voted
NIPS
2008
15 years 4 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
127
Voted
ICDM
2009
IEEE
175views Data Mining» more  ICDM 2009»
15 years 10 days 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
126
Voted
RECOMB
2008
Springer
16 years 2 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...