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» Algorithms for center and Tverberg points
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PODS
2008
ACM
159views Database» more  PODS 2008»
14 years 7 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
IPMI
2007
Springer
14 years 8 months ago
Probabilistic Clustering and Quantitative Analysis of White Matter Fiber Tracts
A novel framework for joint clustering and point-by-point mapping of white matter fiber pathways is presented. Accurate clustering of the trajectories into fiber bundles requires p...
Mahnaz Maddah, William M. Wells III, Simon K. Warf...
ICML
2006
IEEE
14 years 8 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
TKDE
2008
162views more  TKDE 2008»
13 years 7 months ago
Continuous k-Means Monitoring over Moving Objects
Given a dataset P, a k-means query returns k points in space (called centers), such that the average squared distance between each point in P and its nearest center is minimized. S...
Zhenjie Zhang, Yin Yang, Anthony K. H. Tung, Dimit...
SODA
2003
ACM
126views Algorithms» more  SODA 2003»
13 years 8 months ago
Smaller core-sets for balls
We prove the existence of small core-sets for solving approximate k-center clustering and related problems. The size of these core-sets is considerably smaller than the previously...
Mihai Badoiu, Kenneth L. Clarkson