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» Learning Continuous Time Bayesian Networks
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JMLR
2010
157views more  JMLR 2010»
13 years 2 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
ECCV
2004
Springer
14 years 1 months ago
Authentic Emotion Detection in Real-Time Video
Abstract. There is a growing trend toward emotional intelligence in humancomputer interaction paradigms. In order to react appropriately to a human, the computer would need to have...
Yafei Sun, Nicu Sebe, Michael S. Lew, Theo Gevers
IUI
2006
ACM
14 years 1 months ago
Who's asking for help?: a Bayesian approach to intelligent assistance
Automated software customization is drawing increasing attention as a means to help users deal with the scope, complexity, potential intrusiveness, and ever-changing nature of mod...
Bowen Hui, Craig Boutilier
PKDD
2009
Springer
136views Data Mining» more  PKDD 2009»
14 years 2 months ago
Integrating Logical Reasoning and Probabilistic Chain Graphs
Probabilistic logics have attracted a great deal of attention during the past few years. While logical languages have taken a central position in research on knowledge representati...
Arjen Hommersom, Nivea de Carvalho Ferreira, Peter...
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 6 months ago
Modeling and decision making in spatio-temporal processes for environmental surveillance
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...