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» Conjugate Mixture Models for Clustering Multimodal Data
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SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
14 years 11 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
DAGM
1998
Springer
15 years 1 months ago
Discrete Mixture Models for Unsupervised Image Segmentation
This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Jan Puzicha, Joachim M. Buhmann, Thomas Hofmann
KDD
2005
ACM
112views Data Mining» more  KDD 2005»
15 years 10 months ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...
CF
2005
ACM
14 years 11 months ago
Exploiting processor groups to extend scalability of the GA shared memory programming model
Exploiting processor groups is becoming increasingly important for programming next-generation high-end systems composed of tens or hundreds of thousands of processors. This paper...
Jarek Nieplocha, Manojkumar Krishnan, Bruce Palmer...
KDD
1997
ACM
72views Data Mining» more  KDD 1997»
15 years 1 months ago
Detecting Atmospheric Regimes Using Cross-Validated Clustering
Low-frequency variability in geopotential height records of the Northern Hemisphere is a topic of significance in atmospheric science, having profound implications for climate mod...
Padhraic Smyth, Michael Ghil, Kayo Ide, Joseph Rod...