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ICMLA
2008
15 years 7 months ago
Farthest Centroids Divisive Clustering
A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
Haw-ren Fang, Yousef Saad
SAC
2005
ACM
15 years 11 months ago
Node clustering based on link delay in P2P networks
Peer-to-peer (P2P) has become an important computing model because of its adaptation, self-organization and autonomy etc. But efficient organization of the nodes in P2P networks i...
Wei Zheng, Sheng Zhang, Yi Ouyang, Fillia Makedon,...
PODS
2005
ACM
115views Database» more  PODS 2005»
16 years 6 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
ICASSP
2011
IEEE
14 years 10 months ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
ICASSP
2010
IEEE
15 years 6 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld