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» Coarticulation in Markov Decision Processes
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JAIR
2002
120views more  JAIR 2002»
13 years 7 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
ACL
2000
13 years 9 months ago
Spoken Dialogue Management Using Probabilistic Reasoning
Spoken dialogue managers have benefited from using stochastic planners such as Markov Decision Processes (MDPs). However, so far, MDPs do not handle well noisy and ambiguous speec...
Nicholas Roy, Joelle Pineau, Sebastian Thrun
AAAI
2011
12 years 7 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
SIBGRAPI
2000
IEEE
14 years 3 days ago
An Off-Line Signature Verification System using Hidden Markov Model and Cross-Validation
This work has as main objective to present an off-line signature verification system. It is basically divided into three parts. The first one demonstrates a pre-processing process,...
Edson J. R. Justino, Abdenaim El Yacoubi, Fl&aacut...

Publication
151views
12 years 6 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis