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UAI
2004
13 years 9 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
IJCNN
2006
IEEE
14 years 1 months ago
A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...
Yiwen Wang 0002, António R. C. Paiva, Jose ...
MEDINFO
2007
132views Healthcare» more  MEDINFO 2007»
13 years 9 months ago
Comparing Decision Support Methodologies for Identifying Asthma Exacerbations
Objective: To apply and compare common machine learning techniques with an expert-built Bayesian Network to determine eligibility for asthma guidelines in pediatric emergency depa...
Judith W. Dexheimer, Laura E. Brown, Jeffrey Leego...
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...
IJAR
2002
102views more  IJAR 2002»
13 years 7 months ago
Networks of probabilistic events in discrete time
The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
Severino F. Galán, Francisco Javier D&iacut...