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ICML
2006
IEEE
16 years 5 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»
15 years 10 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
15 years 5 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»
15 years 4 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
16 years 5 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