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» Efficient Distance Computation Between Non-Convex Objects
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DAWAK
2006
Springer
13 years 11 months ago
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...
KDD
2006
ACM
142views Data Mining» more  KDD 2006»
14 years 8 months ago
Mining distance-based outliers from large databases in any metric space
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
Yufei Tao, Xiaokui Xiao, Shuigeng Zhou
JMIV
2006
94views more  JMIV 2006»
13 years 8 months ago
Geodesic Shooting for Computational Anatomy
Studying large deformations with a Riemannian approach has been an efficient point of view to generate metrics between deformable objects, and to provide accurate, non ambiguous an...
Michael I. Miller, Alain Trouvé, Laurent Yo...
EMMCVPR
2007
Springer
14 years 20 hour ago
Efficient Shape Matching Via Graph Cuts
Abstract. Meaningful notions of distance between planar shapes typically involve the computation of a correspondence between points on one shape and points on the other. To determi...
Frank R. Schmidt, Eno Töppe, Daniel Cremers, ...
NIPS
2004
13 years 9 months ago
Hierarchical Clustering of a Mixture Model
In this paper we propose an efficient algorithm for reducing a large mixture of Gaussians into a smaller mixture while still preserving the component structure of the original mod...
Jacob Goldberger, Sam T. Roweis