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Using Mixture Models for Collaborative Filtering.
F. Chierichetti, A. Dasgupta, R. Kumar, S. Lattanzi (2015) "On Learning Mixture Models for Permutations", ITCS.
The model is obtained by multiplying Scheffé mixture models for each mixture system.
This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time.
(If mixture models for the prevalences were not used, prevalence estimates might be artificially inflated, especially in herds and regions with low or zero prevalence).
This paper introduces a novel automated anomaly detection method that uses Gaussian Mixture Models for modelling the normal behaviour of employees to detect anomalous behaviour that may be malicious.
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Mixture modeling for dynamic PET data.
Sparsity Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET.
A Dirichlet process mixture model for clustering longitudinal gene expression data.
Sparse Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET.
A mixture model for the departure times is introduced.
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