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117
Voted
UAI
2004
15 years 4 months ago
2004
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
130
Voted
SAC
2006
ACM
15 years 9 months ago
2006
ACM
We present an emotion recognition system based on a probabilistic approach to adaptive processing of Facial Emotion Tree Structures (FETS). FETS are made up of localized Gabor fea...
125
Voted
JCP
2007
15 years 3 months ago
2007
—In this paper, a neural network solution to extract independent components from nonlinearly mixed signals is proposed. Firstly, a structurally constrained mixing model is introd...
133
Voted
AI
2002
Springer
15 years 3 months ago
2002
Springer
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
137
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GIS
2009
ACM
15 years 7 months ago
2009
ACM
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...