Bayesian clustering in decomposable graphs

Luke Bornn; Francois Caron

doi:10.1214/11-ba630

Bayesian clustering in decomposable graphs

Bayesian Analysis ◽

10.1214/11-ba630 ◽

2011 ◽

Vol 6 (4) ◽

pp. 829-846 ◽

Cited By ~ 3

Author(s):

Luke Bornn ◽

Francois Caron

Keyword(s):

Bayesian Clustering ◽

Decomposable Graphs

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Multivariate Bayesian clustering using covariate‐informed components with application to boreal vegetation sensitivity

Biometrics ◽

10.1111/biom.13507 ◽

2021 ◽

Author(s):

Henry R. Scharf ◽

Ann M. Raiho ◽

Sierra Pugh ◽

Carl A. Roland ◽

David K. Swanson ◽

...

Keyword(s):

Bayesian Clustering

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Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Ecography ◽

10.1111/j.0906-7590.2007.05002.x ◽

2007 ◽

Vol 30 (4) ◽

pp. 526-536 ◽

Cited By ~ 21

Author(s):

J. Angus Webb ◽

Nicholas R. Bond ◽

Stephen R. Wealands ◽

Ralph Mac Nally ◽

Gerry P. Quinn ◽

...

Keyword(s):

Bayesian Clustering ◽

Landscape Classification

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Co-SpOT: Cooperative Spectrum Opportunity Detection Using Bayesian Clustering in Spectrum-Heterogeneous Cognitive Radio Networks

IEEE Transactions on Cognitive Communications and Networking ◽

10.1109/tccn.2017.2787710 ◽

2018 ◽

Vol 4 (2) ◽

pp. 206-219 ◽

Cited By ~ 10

Author(s):

Alireza Zaeemzadeh ◽

Mohsen Joneidi ◽

Nazanin Rahnavard ◽

Guo-Jun Qi

Keyword(s):

Cognitive Radio ◽

Cognitive Radio Networks ◽

Radio Networks ◽

Bayesian Clustering

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Design of multiple-level hybrid classifier for intrusion detection system using Bayesian clustering and decision trees

Pattern Recognition Letters ◽

10.1016/j.patrec.2008.01.008 ◽

2008 ◽

Vol 29 (7) ◽

pp. 918-924 ◽

Cited By ~ 89

Author(s):

Cheng Xiang ◽

Png Chin Yong ◽

Lim Swee Meng

Keyword(s):

Intrusion Detection ◽

Decision Trees ◽

Intrusion Detection System ◽

Detection System ◽

Bayesian Clustering ◽

Multiple Level ◽

Hybrid Classifier

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Wishart distributions for decomposable graphs

The Annals of Statistics ◽

10.1214/009053606000001235 ◽

2007 ◽

Vol 35 (3) ◽

pp. 1278-1323 ◽

Cited By ~ 46

Author(s):

Gérard Letac ◽

Hélène Massam

Keyword(s):

Wishart Distributions ◽

Decomposable Graphs

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Bayesian clustering methods for morphological analysis of MR images

Proceedings IEEE International Symposium on Biomedical Imaging ◽

10.1109/isbi.2002.1029399 ◽

2003 ◽

Cited By ~ 1

Author(s):

Hanchuan Peng ◽

E. Herskovits ◽

C. Davatzikos

Keyword(s):

Morphological Analysis ◽

Bayesian Clustering ◽

Clustering Methods ◽

Mr Images

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Bayesian clustering and tracking of neuronal signals for autonomous neural interfaces

2008 47th IEEE Conference on Decision and Control ◽

10.1109/cdc.2008.4739362 ◽

2008 ◽

Cited By ~ 5

Author(s):

Michael T. Wolf ◽

Joel W. Burdick

Keyword(s):

Neural Interfaces ◽

Bayesian Clustering

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Decomposable graphs and hypergraphs

Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics ◽

10.1017/s1446788700027300 ◽

1984 ◽

Vol 36 (1) ◽

pp. 12-29 ◽

Cited By ~ 46

Author(s):

S. L. Lauritzen ◽

T. P. Speed ◽

K. Vijayan

Keyword(s):

Combinatorial Identity ◽

Decomposable Graphs

AbstractWe define and investigate the notion of a decomposable hypergraph, showing that such a hypergraph always is conformal, that is, can be viewed as the class of maximal cliques of a graph. We further show that the clique hypergraph of a graph is decomposable if and only if the graph is triangulated and characterise such graphs in terms of a combinatorial identity.

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