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JMLR
2012
13 years 8 months ago
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Martin Schiegg, Marion Neumann, Kristian Kersting
ICML
1996
IEEE
16 years 7 months ago
Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Kazuo J. Ezawa, Moninder Singh, Steven W. Norton
BMCBI
2005
178views more  BMCBI 2005»
15 years 6 months ago
A quantization method based on threshold optimization for microarray short time series
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
DIAGRAMS
2004
Springer
15 years 11 months ago
Bayesian Boxes: A Colored Calculator for Picturing Posteriors
The need for Bayesian inference arises in military intelligence, medical diagnosis and many other practical applications. The problem is that human inferences are generally conserv...
Kevin Burns
SIBGRAPI
2008
IEEE
16 years 19 days ago
Bayesian Estimation of Hyperparameters in MRI through the Maximum Evidence Method
Bayesian inference methods are commonly applied to the classification of brain Magnetic Resonance images (MRI). We use the Maximum Evidence (ME) approach to estimate the most prob...
Damian E. Oliva, Roberto A. Isoardi, Germán...