Výsledky vyhledávání - "Generalized expectation-maximization algorithm"

Multiple testing for neuroimaging via hidden Markov random field Autor Shu, Hai, Nan, Bin, Koeppe, Robert

“… A generalized expectation–maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters…”
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Estimating properties of the fast and slow adaptive processes during sensorimotor adaptation Autor Albert, Scott T, Shadmehr, Reza

“…Experience of a prediction error recruits multiple motor learning processes, some that learn strongly from error but have weak retention and some that learn…”
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Impact of prior specifications in a shrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction Autor Knürr, Timo, Läärä, Esa, Sillanpää, Mikko J

“… results is subject to misspecified assumptions because of weak biological prior evidence…”
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Impact of prior specifications in ashrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction Autor Knuerr, Timo, Laeaerae, Esa, Sillanpaeae, Mikko J

“… results is subject to misspecified assumptions because of weak biological prior evidence…”
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Predictors with measurement error in mixtures of polynomial regressions Autor Fang, Xiaoqiong, Chen, Andy W., Young, Derek S.

“…There has been a substantial body of research on mixtures-of-regressions models that has developed over the past 20 years. While much of the recent literature…”
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Simultaneous Gaussian model-based clustering for samples of multiple origins Autor Lourme, A., Biernacki, C.

“…-called simultaneous clustering method. Maximum likelihood mixture parameters, subject to the linear link constraint, can be easily…”
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Multiple Testing for Neuroimaging via Hidden Markov Random Field Autor Shu, Hai, Bin Nan, Koeppe, Robert

“… A generalized expectation-maximization algorithm for maximizing the penalized likelihood is proposed for estimating the model parameters…”
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Local and global models for articulated motion analysis Autor Wagg, D.K

“…Vision is likely the most important of the senses employed by humans in understanding their environment, but computer systems are still sorely lacking in this…”
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