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ICML
2006
IEEE
14 years 10 months ago
Learning the structure of Factored Markov Decision Processes in reinforcement learning problems
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...
ICDM
2008
IEEE
120views Data Mining» more  ICDM 2008»
14 years 3 months ago
Prediction of Skin Penetration Using Machine Learning Methods
Improving predictions of the skin permeability coefficient is a difficult problem. It is also an important issue with the increasing use of skin patches as a means of drug deliv...
Yi Sun, Gary P. Moss, Maria Prapopoulou, Rod Adams...
NIPS
2004
13 years 10 months ago
Semi-supervised Learning with Penalized Probabilistic Clustering
While clustering is usually an unsupervised operation, there are circumstances in which we believe (with varying degrees of certainty) that items A and B should be assigned to the...
Zhengdong Lu, Todd K. Leen
CORR
2008
Springer
147views Education» more  CORR 2008»
13 years 9 months ago
A Minimum Relative Entropy Principle for Learning and Acting
This paper proposes a method to construct an adaptive agent that is universal with respect to a given class of experts, where each expert is designed specifically for a particular...
Pedro A. Ortega, Daniel A. Braun
ICPR
2002
IEEE
14 years 10 months ago
Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification
In this paper, we propose a new context-sensitive Bayesian learning algorithm. By modeling the distributions of data locations by a mixture of Gaussians, the new algorithm can uti...
Yuan (Alan) Qi, Rosalind W. Picard