We solve the resulting MLE problem using an expectation maximization (EM) algorithm, tailored for the nonlinear model, and provide a numerically robust implementation. The proposed method is ...

Keywords: expectation-maximization (EM), majorization-minimization (MM), alternating least squares (ALS), tensor networks, tensor train, logistic regression, Pólya-Gamma (PG) augmentation Citation: ...

Zakkour, A., Perret, C. and Slaoui, Y. (2023) Stochastic Expectation Maximization Algorithm for Linear Mixed-Effects Model with Interactions in the Presence of Incomplete Data. Entropy, 25, Article ...

This article is concerned with the problem of remote state estimation for linear discrete-time systems with packet dropouts. The packet dropouts are state dependent, which occur only when the ...

The combination of the MM algorithm and ALS ensures that the objective function decreases monotonically. The proposed algorithm can also be said to be expectation maximization (EM) in the sense of ...

The Intelligent Battery Cycle Life Maximization Algorithm leverages machine learning to monitor and adjust battery behavior in real time.

Article citations More>> Korting, T. S., Dutra, L. V., Fonseca, L. M. G., Erthal, G., & da Silva, F. C. (2007) Improvements to Expectation-Maximization Approach for Unsupervised Classification of ...

This repository provides tools and algorithms for the estimation of mixture models for mixed-type data. The algorithms jointly estimate the model parameters and the number of classes in the model.