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» Clustering for metric and nonmetric distance measures
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SDM
2007
SIAM
201views Data Mining» more  SDM 2007»
15 years 1 months ago
Fast Best-Match Shape Searching in Rotation Invariant Metric Spaces
Object recognition and content-based image retrieval systems rely heavily on the accurate and efficient identification of shapes. A fundamental requirement in the shape analysis ...
Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng...
TMM
2008
201views more  TMM 2008»
14 years 11 months ago
Fast Best-Match Shape Searching in Rotation-Invariant Metric Spaces
Object recognition and content-based image retrieval systems rely heavily on the accurate and efficient identification of shapes. A fundamental requirement in the shape analysis p...
Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng...
JCSS
2002
199views more  JCSS 2002»
14 years 11 months ago
A Constant-Factor Approximation Algorithm for the k-Median Problem
We present the first constant-factor approximation algorithm for the metric k-median problem. The k-median problem is one of the most well-studied clustering problems, i.e., those...
Moses Charikar, Sudipto Guha, Éva Tardos, D...
CORR
2010
Springer
81views Education» more  CORR 2010»
14 years 6 months ago
Analysis of Agglomerative Clustering
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
Marcel R. Ackermann, Johannes Blömer, Daniel ...
RECOMB
2009
Springer
16 years 11 days ago
Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
Abstract. Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotation information for som...
Saket Navlakha, James Robert White, Niranjan Nagar...