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ML
2002
ACM
246views Machine Learning» more  ML 2002»
13 years 7 months ago
Bayesian Clustering by Dynamics
This paper introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to disc...
Marco Ramoni, Paola Sebastiani, Paul R. Cohen
AI
2006
Springer
13 years 7 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
BMCBI
2006
163views more  BMCBI 2006»
13 years 7 months ago
Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological featur
Background: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a userdefined list of genes and/or proteins. The strategy exploits annotation data ...
J. R. Semeiks, A. Rizki, Mina J. Bissell, I. Saira...
TASLP
2010
128views more  TASLP 2010»
13 years 2 months ago
Speaker Diarization Exploiting the Eigengap Criterion and Cluster Ensembles
A novel system for speaker diarization is proposed that combines the eigengap criterion and cluster ensembles. No explicit assumptions on the number of speakers are made. Two varia...
Nikoletta Bassiou, Vassiliki Moschou, Constantine ...
ECML
2006
Springer
13 years 11 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi