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RSKT
2009
Springer
14 years 4 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao
FCS
2006
13 years 11 months ago
Principles of Optimal Probabilistic Decision Tree Construction
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
ICML
2007
IEEE
14 years 10 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan
DEXA
2005
Springer
106views Database» more  DEXA 2005»
14 years 3 months ago
Personalized and Community Decision Support in eTourism Intermediaries
The rapidly growing web technologies and electronic commerce applications have stimulated the need of personalized and group decision support functionalities in eTourism intermedia...
Chien-Chih Yu
ECSQARU
2007
Springer
14 years 3 months ago
Shared Ordered Binary Decision Diagrams for Dempster-Shafer Theory
The binary representation is widely used for representing focal sets of Dempster-Shafer belief functions because it allows to compute efficiently all relevant operations. However, ...
Norbert Lehmann