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JAIR
2006
138views more  JAIR 2006»
14 years 9 months ago
Logical Hidden Markov Models
Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characte...
Kristian Kersting, Luc De Raedt, Tapani Raiko
68
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JCT
2007
83views more  JCT 2007»
14 years 9 months ago
A finiteness theorem for Markov bases of hierarchical models
We show that the complexity of the Markov bases of multidimensional tables stabilizes eventually if a single table dimension is allowed to vary. In particular, if this table dimen...
Serkan Hosten, Seth Sullivant
ANSS
2006
IEEE
15 years 3 months ago
A New Approach for Computing Conditional Probabilities of General Stochastic Processes
In this paper Hidden Markov Model algorithms are considered as a method for computing conditional properties of continuous-time stochastic simulation models. The goal is to develo...
Fabian Wickborn, Claudia Isensee, Thomas Simon, Sa...
ECCV
2010
Springer
15 years 2 months ago
Learning What and How of Contextual Models for Scene Labeling
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
APN
2007
Springer
15 years 3 months ago
Markov Decision Petri Net and Markov Decision Well-Formed Net Formalisms
In this work, we propose two high-level formalisms, Markov Decision Petri Nets (MDPNs) and Markov Decision Well-formed Nets (MDWNs), useful for the modeling and analysis of distrib...
Marco Beccuti, Giuliana Franceschinis, Serge Hadda...