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ICML
2007
IEEE
16 years 7 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ICML
2006
IEEE
16 years 7 months ago
Bayesian pattern ranking for move prediction in the game of Go
We investigate the problem of learning to predict moves in the board game of Go from game records of expert players. In particular, we obtain a probability distribution over legal...
David H. Stern, Ralf Herbrich, Thore Graepel
ICML
1998
IEEE
16 years 7 months ago
Heading in the Right Direction
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
Hagit Shatkay, Leslie Pack Kaelbling
ICML
2009
IEEE
16 years 1 months ago
Grammatical inference as a principal component analysis problem
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Raphaël Bailly, François Denis, Liva R...
IPPS
2009
IEEE
16 years 29 days ago
Enabling high-performance memory migration for multithreaded applications on LINUX
As the number of cores per machine increases, memory architectures are being redesigned to avoid bus contention and sustain higher throughput needs. The emergence of Non-Uniform M...
Brice Goglin, Nathalie Furmento