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KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 6 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
ICCV
2009
IEEE
16 years 11 months ago
Mode-Detection via Median-Shift
Median-shift is a mode seeking algorithm that relies on computing the median of local neighborhoods, instead of the mean. We further combine median-shift with Locality Sensitive...
Lior Shapira, Shai Avidan, Ariel Shamir
MICCAI
2007
Springer
16 years 7 months ago
Shape Analysis Using a Point-Based Statistical Shape Model Built on Correspondence Probabilities
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
CLUSTER
2008
IEEE
16 years 24 days ago
Enabling lock-free concurrent fine-grain access to massive distributed data: Application to supernovae detection
—We consider the problem of efficiently managing massive data in a large-scale distributed environment. We consider data strings of size in the order of Terabytes, shared and ac...
Bogdan Nicolae, Gabriel Antoniu, Luc Bougé
DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
15 years 10 months ago
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...