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» Bias and Variance Approximation in Value Function Estimates
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SSPR
2000
Springer
14 years 6 days ago
A New Approximation Method of the Quadratic Discriminant Function
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...
Shinichiro Omachi, Fang Sun, Hirotomo Aso
WSC
2000
13 years 10 months ago
Analyzing transformation-based simulation metamodels
We present a technique for analyzing a simulation metamodel that has been constructed using a variancestabilizing transformation. To compute a valid confidence interval for the ex...
Maria de los A. Irizarry, Michael E. Kuhl, Emily K...
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
14 years 9 days ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
ISBI
2004
IEEE
14 years 9 months ago
Covariance of Kinetic Parameter Estimators Based on Time Activity Curve Reconstructions: Preliminary Study on 1D Dynamic Imaging
We provide approximate expressions for the covariance matrix of kinetic parameter estimators based on time activity curve (TAC) reconstructions when TACs are modeled as a linear c...
Sangtae Ahn, Jeffrey A. Fessler, Thomas E. Nichols...
ATAL
2007
Springer
14 years 2 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone