Výsledky vyhledávání - "Alternating Expectation Conditional Maximization algorithm"

Fast Matrix-Free Methods for Model-Based Personalized Synthetic MR Imaging Autor Pal, Subrata, Dutta, Somak, Maitra, Ranjan

“…Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the…”
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Estimating basis functions in massive fields under the spatial mixed effects model Autor Pazdernik, Karl, Maitra, Ranjan

“…Spatial prediction is commonly achieved under the assumption of a Gaussian random field by obtaining maximum likelihood estimates of parameters, and then using…”
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Flexible High-Dimensional Unsupervised Learning with Missing Data Autor Wei, Yuhong, Tang, Yang, McNicholas, Paul D.

“…The mixture of factor analyzers (MFA) model is a famous mixture model-based approach for unsupervised learning with high-dimensional data. It can be useful,…”
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Mixtures of skew-t factor analyzers Autor Murray, Paula M., Browne, Ryan P., McNicholas, Paul D.

“… The alternating expectation–conditional maximization algorithm is used for model parameter estimation and the Bayesian information criterion is used for model selection…”
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Robust clustering of multiply censored data via mixtures of t factor analyzers Autor Wang, Wan-Lun, Lin, Tsung-I

“… For maximum likelihood estimation, we construct an alternating expectation conditional maximization algorithm in which the E-step relies on the first-two moments of truncated multivariate…”
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The EM Algorithm-an Old Folk-song Sung to a Fast New Tune Autor Meng, Xiao-Li, Van Dyk, David

“…–conditional maximization algorithm AECM that couples flexible data augmentation schemes with model reduction schemes to achieve efficient computations…”
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Cluster-weighted ...-factor analyzers for robust model-based clustering and dimension reduction Autor Subedi, Sanjeena, Punzo, Antonio, Ingrassia, Salvatore, Mcnicholas, Paul D

“… A family of twenty parsimonious variants of this model is also presented and the alternating expectation-conditional maximization algorithm, for maximum likelihood estimation of the parameters…”
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A robust factor analysis model based on the canonical fundamental skew-t distribution Autor Lin, Tsung-I, Chen, I-An, Wang, Wan-Lun

“… An efficient alternating expectation conditional maximization algorithm fabricated under several reduced complete-data spaces is developed to estimate…”
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Cluster-weighted t-factor analyzers for robust model-based clustering and dimension reduction Autor Subedi, Sanjeena, Punzo, Antonio, Ingrassia, Salvatore, McNicholas, Paul D.

“… A family of twenty parsimonious variants of this model is also presented and the alternating expectation-conditional maximization algorithm, for maximum likelihood estimation of the parameters…”
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Extending mixtures of multivariate t-factor analyzers Autor Andrews, Jeffrey L., McNicholas, Paul D.

“…-conditional maximization algorithm and convergence is determined…”
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Extending Cluster-Weighted Factor Analyzers for Multivariate Prediction and Interpretability Autor Qin, Xiaoke, Martella, Francesca, Subedi, Sanjeena

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Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values Autor Wang, Wan-Lun

“… Under a missing at random mechanism, a pseudo-data version of the alternating expectation-conditional maximization algorithm is developed to carry out maximum likelihood estimation and impute missing…”
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Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data Autor Tu, Wangshu, Subedi, Sanjeena

“…The human microbiome plays an important role in human health and disease status. Next-generating sequencing technologies allow for quantifying the composition…”
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Clustering and classification via cluster-weighted factor analyzers Autor Subedi, Sanjeena, Punzo, Antonio, Ingrassia, Salvatore, McNicholas, Paul D.

“… The alternating expectation-conditional maximization algorithm, for maximum likelihood…”
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A mixture of generalized hyperbolic factor analyzers Autor Tortora, Cristina, McNicholas, Paul D., Browne, Ryan P.

“… An alternating expectation-conditional maximization algorithm is used for parameter estimation, and the Bayesian information criterion is used to select the number of factors as well as the number of components…”
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Extending Cluster-Weighted Factor Analyzers for multivariate prediction and high-dimensional interpretability Autor Qin, Xiaoke, Martella, Francesca, Subedi, Sanjeena

“… An alternating expectation-conditional maximization algorithm is employed for parameter…”
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Mixtures of Common Skew-t Factor Analyzers Autor Murray, Paula M, McNicholas, Paul D, Browne, Ryan P

“… The alternating expectation-conditional maximization algorithm is employed for parameter estimation…”
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Mixtures of Skew-t Factor Analyzers Autor Murray, Paula M, Browne, Ryan P, McNicholas, Paul D

“… The alternating expectation-conditional maximization algorithm is used for model parameter estimation and the Bayesian information criterion is used for model selection…”
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Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data Autor Tu, Wangshu, Subedi, Sanjeena

“…The human microbiome plays an important role in human health and disease status. Next generating sequencing technologies allow for quantifying the composition…”
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Clustering and Classification via Cluster-Weighted Factor Analyzers Autor Subedi, Sanjeena, Punzo, Antonio, Ingrassia, Salvatore, McNicholas, Paul D

“… The alternating expectation-conditional maximization algorithm, for maximum likelihood estimation of the parameters of all the…”
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