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EOR
2006
113views more  EOR 2006»
14 years 9 months ago
Validation of regression metamodels in simulation: Bootstrap approach
Simulation experiments are often analyzed through a linear regression model of their input/output data. Such an analysis yields a metamodel or response surface for the underlying ...
Jack P. C. Kleijnen, David Deflandre
CSDA
2007
81views more  CSDA 2007»
14 years 9 months ago
A stochastic EM algorithm for a semiparametric mixture model
Recently, there has been a considerable interest in finite mixture models with semi-/non-parametric component distributions. Identifiability of such model parameters is generall...
Laurent Bordes, Didier Chauveau, Pierre Vandekerkh...
ICCV
2003
IEEE
15 years 11 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
IPMI
2007
Springer
15 years 10 months ago
Maximum Likelihood Estimators in Magnetic Resonance Imaging
Images of the MRI signal intensity are normally constructed by taking the magnitude of the complex-valued data. This results in a biased estimate of the true signal intensity. We c...
M. Dylan Tisdall, M. Stella Atkins, R. A. Lockhart
ICML
2007
IEEE
15 years 10 months ago
Most likely heteroscedastic Gaussian process regression
This paper presents a novel Gaussian process (GP) approach to regression with inputdependent noise rates. We follow Goldberg et al.'s approach and model the noise variance us...
Kristian Kersting, Christian Plagemann, Patrick Pf...