Expectation maximization and complex duration distributions for continuous time Bayesian networks

Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence, UAI 2005

Volumn , Issue , 2005, Pages 421-430

  Nodelman, Uri ^a   Shelton, Christian R ^b   Koller, Daphne ^a  

^a STANFORD UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; MARKOV PROCESSES; MAXIMUM PRINCIPLE; STOCHASTIC SYSTEMS;

CONTINUOUS TIME MARKOV PROCESS; CONTINUOUS-TIME; DEPENDENCY GRAPHS; EXPECTATION - MAXIMIZATIONS; EXPECTATION MAXIMIZATION; PHASE DISTRIBUTION; TRANSITION DURATION; TRANSITION MODEL;

CONTINUOUS TIME SYSTEMS;

EID: 77958587560     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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