7 papers
Approximation rates for finite mixtures of location-scale models and fast least-squares estimators
Hien Duy Nguyen, TrungTin Nguyen, Jacob Westerhout +1
Finite mixture models provide a flexible framework for approximating and estimating multivariate probability densities. We study mixtures formed from translated and rescaled copies…
Modifications of the BIC for order selection in finite mixture models
Hien Duy Nguyen, TrungTin Nguyen
Finite mixture models are ubiquitous in modern statistical modeling, and a recurring practical issue is choosing the model order. In \citet[SankhyÄ Series A, \textbf62, pp. 49--66…
Revisiting Incremental Stochastic Majorization-Minimization Algorithms with Applications to Mixture of Experts
TrungKhang Tran, TrungTin Nguyen, Gersende Fort +5
Processing high-volume, streaming data is increasingly common in modern statistics and machine learning, where batch-mode algorithms are often impractical because they require repe…
On the large-sample limits of some Bayesian model evaluation statistics
Hien Duy Nguyen, Mayetri Gupta, Jacob Westerhout +1
Model selection and order selection problems frequently arise in statistical practice. A popular approach to addressing these problems in the frequentist setting involves informati…
Risk Bounds for Mixture Density Estimation on Compact Domains via the -Lifted Kullback--Leibler Divergence
Mark Chiu Chong, Hien Duy Nguyen, TrungTin Nguyen
We consider the problem of estimating probability density functions based on sample data, using a finite mixture of densities from some component class. To this end, we introduce t…
Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts
TrungTin Nguyen, Hien D Nguyen, Faicel Chamroukhi +1
We investigate the estimation properties of the mixture of experts (MoE) model in a high-dimensional setting, where the number of predictors is much larger than the sample size, an…