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ECML
2005
Springer
13 years 11 months ago
Inducing Hidden Markov Models to Model Long-Term Dependencies
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Jérôme Callut, Pierre Dupont
ICML
1999
IEEE
14 years 6 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
PAMI
2007
186views more  PAMI 2007»
13 years 5 months ago
Value-Directed Human Behavior Analysis from Video Using Partially Observable Markov Decision Processes
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...
Jesse Hoey, James J. Little
SIGMETRICS
2002
ACM
107views Hardware» more  SIGMETRICS 2002»
13 years 5 months ago
Passage time distributions in large Markov chains
Probability distributions of response times are important in the design and analysis of transaction processing systems and computercommunication systems. We present a general tech...
Peter G. Harrison, William J. Knottenbelt