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IJAR
2010
152views more  IJAR 2010»
13 years 7 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
DEXAW
2010
IEEE
179views Database» more  DEXAW 2010»
13 years 10 months ago
Flexible, Robust and Dynamic Dialogue Modeling with a Speech Dialogue Interface for Controlling a Hi-Fi Audio System
This work is focused on the context of speech interfaces for controlling household electronic devices. In particular, we present an example of a spoken dialogue system for controll...
Fernando F. Fernández-Martínez, Javi...
CLADE
2008
IEEE
14 years 3 months ago
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Xinghua Shi, Rick Stevens
IJCNN
2006
IEEE
14 years 3 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
JCB
2007
198views more  JCB 2007»
13 years 9 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III