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ICML
2005
IEEE
16 years 2 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
15 years 11 months ago
CORE: Nonparametric Clustering of Large Numeric Databases.
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
Andrej Taliun, Arturas Mazeika, Michael H. Bö...
IPPS
2006
IEEE
15 years 7 months ago
Empowering a helper cluster through data-width aware instruction selection policies
Narrow values that can be represented by less number of bits than the full machine width occur very frequently in programs. On the other hand, clustering mechanisms enable cost- a...
Osman S. Unsal, Oguz Ergin, Xavier Vera, Antonio G...
ECCV
2010
Springer
15 years 4 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 5 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen