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87
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ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
86
Voted
IJCAI
2007
14 years 11 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
AAAI
2010
14 years 11 months ago
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
Ian Porteous, Arthur Asuncion, Max Welling
CSDA
2008
77views more  CSDA 2008»
14 years 9 months ago
Maximizing equity market sector predictability in a Bayesian time-varying parameter model
A large body of evidence has emerged in recent studies confirming that macroeconomic factors play an important role in determining investor risk premia and the ultimate path of eq...
Lorne D. Johnson, Georgios Sakoulis
90
Voted
CORR
2000
Springer
96views Education» more  CORR 2000»
14 years 9 months ago
A Bayesian Reflection on Surfaces
: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informativ...
David R. Wolf