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99
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ICML
2009
IEEE
16 years 1 months ago
Near-Bayesian exploration in polynomial time
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
J. Zico Kolter, Andrew Y. Ng
JMLR
2000
134views more  JMLR 2000»
15 years 16 days ago
Learning with Mixtures of Trees
This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu...
Marina Meila, Michael I. Jordan
115
Voted
IJAR
2010
152views more  IJAR 2010»
14 years 11 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
88
Voted
ICIP
2010
IEEE
14 years 10 months ago
Hyperspectral image segmentation and unmixing using hidden Markov trees
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors. We hypothesize that hy...
Roni Mittelman, Alfred O. Hero III
81
Voted
CORR
2006
Springer
98views Education» more  CORR 2006»
15 years 23 days ago
Bayesian Regression of Piecewise Constant Functions
We derive an exact and efficient Bayesian regression algorithm for piecewise constant functions of unknown segment number, boundary location, and levels. It works for any noise an...
Marcus Hutter