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PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
14 years 1 months ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
HICSS
2009
IEEE
128views Biometrics» more  HICSS 2009»
14 years 26 days ago
Cyber Security Risks Assessment with Bayesian Defense Graphs and Architectural Models
To facilitate rational decision making regarding cyber security investments, decision makers need to be able to assess expected losses before and after potential investments. This...
Teodor Sommestad, Mathias Ekstedt, Pontus Johnson
ILP
2000
Springer
14 years 17 days ago
Bayesian Logic Programs
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...
Kristian Kersting, Luc De Raedt
ACCV
2010
Springer
13 years 11 months ago
Identifying Surprising Events in Videos Using Bayesian Topic Models
Automatic processing of video data is essential in order to allow efficient access to large amounts of video content, a crucial point in such applications as video mining and surve...
Avishai Hendel, Daphna Weinshall, Shmuel Peleg
AAAI
2008
13 years 11 months ago
Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
Cédric Rose, Jamal Saboune, François...