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» Parameter learning for relational Bayesian networks
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ICML
2003
IEEE
15 years 10 months ago
The Use of the Ambiguity Decomposition in Neural Network Ensemble Learning Methods
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
Gavin Brown, Jeremy L. Wyatt
JMLR
2011
167views more  JMLR 2011»
14 years 4 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
EWSN
2004
Springer
15 years 9 months ago
Context-Aware Sensors
Wireless sensor networks typically consist of a large number of sensor nodes embedded in a physical space. Such sensors are low-power devices that are primarily used for monitoring...
Eiman Elnahrawy, Badri Nath
RECOMB
2007
Springer
15 years 10 months ago
A Bayesian Model That Links Microarray mRNA Measurements to Mass Spectrometry Protein Measurements
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
Anitha Kannan, Andrew Emili, Brendan J. Frey
AIEDU
2005
185views more  AIEDU 2005»
14 years 9 months ago
A Bayesian Student Model without Hidden Nodes and its Comparison with Item Response Theory
The Bayesian framework offers a number of techniques for inferring an individual's knowledge state from evidence of mastery of concepts or skills. A typical application where ...
Michel C. Desmarais, Xiaoming Pu