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stat.ML2022
Riemannian Optimization for Variance Estimation in Linear Mixed Models
Lena Sembach, Jan Pablo Burgard, Volker H. Schulz
Variance parameter estimation in linear mixed models is a challenge for many classical nonlinear optimization algorithms due to the positive-definiteness constraint of the random e…
stat.ML2021★ 4 cited
A Riemannian Newton Trust-Region Method for Fitting Gaussian Mixture Models
Lena Sembach, Jan Pablo Burgard, Volker H. Schulz
Gaussian Mixture Models are a powerful tool in Data Science and Statistics that are mainly used for clustering and density approximation. The task of estimating the model parameter…