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ICML
2006
IEEE
16 years 7 months ago
Combined central and subspace clustering for computer vision applications
Central and subspace clustering methods are at the core of many segmentation problems in computer vision. However, both methods fail to give the correct segmentation in many pract...
Le Lu, René Vidal
ACST
2006
15 years 8 months ago
Distributed hierarchical document clustering
This paper investigates the applicability of distributed clustering technique, called RACHET [1], to organize large sets of distributed text data. Although the authors of RACHET c...
Debzani Deb, M. Muztaba Fuad, Rafal A. Angryk
PAMI
2008
197views more  PAMI 2008»
15 years 6 months ago
LEGClust - A Clustering Algorithm Based on Layered Entropic Subgraphs
Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity meas...
Jorge M. Santos, Joaquim Marques de Sá, Lu&...
JUCS
2007
136views more  JUCS 2007»
15 years 6 months ago
VCA: An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks
: Clustering provides an effective mechanism for energy-efficient data delivery in wireless sensor networks. To reduce communication cost, most clustering algorithms rely on a sens...
Min Qin, Roger Zimmermann
PR
2010
156views more  PR 2010»
15 years 5 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...