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ICCV
2005
IEEE
16 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICDE
2009
IEEE
157views Database» more  ICDE 2009»
16 years 1 months ago
Clustering Uncertain Data with Possible Worlds
The topic of managing uncertain data has been explored in many ways. Different methodologies for data storage and query processing have been proposed. As the availability of manag...
Peter Benjamin Volk, Frank Rosenthal, Martin Hahma...
CASCON
1992
134views Education» more  CASCON 1992»
15 years 7 months ago
Cluster busting in anchored graph drawing
Given a graph G and a drawing or layout of G, it is sometimes desirable to alter or adjust the layout. The challenging aspect of designing layout adjustment algorithms is to maint...
Kelly A. Lyons
TKDE
2010
251views more  TKDE 2010»
15 years 4 months ago
Clustering Uncertain Data Using Voronoi Diagrams and R-Tree Index
—We study the problem of clustering uncertain objects whose locations are described by probability density functions (pdf). We show that the UK-means algorithm, which generalises...
Ben Kao, Sau Dan Lee, Foris K. F. Lee, David Wai-L...
EVOW
2006
Springer
15 years 10 months ago
Mining Structural Databases: An Evolutionary Multi-Objetive Conceptual Clustering Methodology
Abstract. The increased availability of biological databases containing representations of complex objects permits access to vast amounts of data. In spite of the recent renewed in...
Rocío Romero-Záliz, Cristina Rubio-E...