4 citations · 5 across the 3 of their papers we have counts for
3 papers
A globally convergent algorithm for lasso-penalized mixture of linear regression models
Luke R. Lloyd-Jones, Hien D. Nguyen, Geoffrey J. McLachlan
Variable selection is an old and pervasive problem in regression analysis. One solution is to impose a lasso penalty to shrink parameter estimates toward zero and perform continuou…
A Block Minorization--Maximization Algorithm for Heteroscedastic Regression
Hien D. Nguyen, Luke R. Lloyd-Jones, Geoffrey J. McLachlan
The computation of the maximum likelihood (ML) estimator for heteroscedastic regression models is considered. The traditional Newton algorithms for the problem require matrix multi…
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…