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Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models
Faïcel Chamroukhi, Florian Lecocq, Hien D. Nguyen
Mixtures-of-Experts models and their maximum likelihood estimation (MLE) via the EM algorithm have been thoroughly studied in the statistics and machine learning literature. They a…
Model-Based Clustering and Classification of Functional Data
Faicel Chamroukhi, Hien D. Nguyen
The problem of complex data analysis is a central topic of modern statistical science and learning systems and is becoming of broader interest with the increasing prevalence of hig…
An Introduction to the Practical and Theoretical Aspects of Mixture-of-Experts Modeling
Hien D. Nguyen, Faicel Chamroukhi
Mixture-of-experts (MoE) models are a powerful paradigm for modeling of data arising from complex data generating processes (DGPs). In this article, we demonstrate how different Mo…
A Universal Approximation Theorem for Mixture of Experts Models
Hien D Nguyen, Luke R Lloyd-Jones, Geoffrey J McLachlan
The mixture of experts (MoE) model is a popular neural network architecture for nonlinear regression and classification. The class of MoE mean functions is known to be uniformly co…