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» Bias and Variance Approximation in Value Function Estimates
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AMC
2007
93views more  AMC 2007»
13 years 8 months ago
Radar network scanning coordination based on ensemble transform Kalman filtering variance optimization
In this work the variance of the error of analyzed wind fields obtained from an ensemble Kalman filter is used as a criterion with which to optimize radar network scanning strat...
Luther White, Alan Shapiro
BMCBI
2006
118views more  BMCBI 2006»
13 years 8 months ago
Microarray image analysis: background estimation using quantile and morphological filters
Background: In a microarray experiment the difference in expression between genes on the same slide is up to 103 fold or more. At low expression, even a small error in the estimat...
Anders Bengtsson, Henrik Bengtsson
ICDM
2003
IEEE
99views Data Mining» more  ICDM 2003»
14 years 1 months ago
Simple Estimators for Relational Bayesian Classifiers
In this paper we present the Relational Bayesian Classifier (RBC), a modification of the Simple Bayesian Classifier (SBC) for relational data. There exist several Bayesian classif...
Jennifer Neville, David Jensen, Brian Gallagher
MP
2006
107views more  MP 2006»
13 years 8 months ago
Convergence theory for nonconvex stochastic programming with an application to mixed logit
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Fabian Bastin, Cinzia Cirillo, Philippe L. Toint
ECML
2004
Springer
14 years 2 months ago
Filtered Reinforcement Learning
Reinforcement learning (RL) algorithms attempt to assign the credit for rewards to the actions that contributed to the reward. Thus far, credit assignment has been done in one of t...
Douglas Aberdeen