71 citations · 96 across the 13 of their papers we have counts for
15 papers
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…
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[Sankhyā Series A, \textbf62, pp. 49--66]…
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…
ExGra-Med: Extended Context Graph Alignment for Medical Vision-Language Models
Duy M. H. Nguyen, Nghiem T. Diep, Trung Q. Nguyen +10
State-of-the-art medical multi-modal LLMs (med-MLLMs), such as LLaVA-Med and BioMedGPT, primarily depend on scaling model size and data volume, with training driven largely by auto…
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…
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen +1
Mixture-of-experts (MoE) model incorporates the power of multiple submodels via gating functions to achieve greater performance in numerous regression and classification applicatio…
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts
Huy Nguyen, TrungTin Nguyen, Khai Nguyen +1
Originally introduced as a neural network for ensemble learning, mixture of experts (MoE) has recently become a fundamental building block of highly successful modern deep neural n…
Demystifying Softmax Gating Function in Gaussian Mixture of Experts
Huy Nguyen, TrungTin Nguyen, Nhat Ho
Understanding the parameter estimation of softmax gating Gaussian mixture of experts has remained a long-standing open problem in the literature. It is mainly due to three fundamen…
Non-asymptotic model selection in block-diagonal mixture of polynomial experts models
TrungTin Nguyen, Faicel Chamroukhi, Hien Duy Nguyen +1
Model selection, via penalized likelihood type criteria, is a standard task in many statistical inference and machine learning problems. Progress has led to deriving criteria with…
A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models
TrungTin Nguyen, Hien Duy Nguyen, Faicel Chamroukhi +1
Mixture of experts (MoE) are a popular class of statistical and machine learning models that have gained attention over the years due to their flexibility and efficiency. In this w…
Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models
Hien Duy Nguyen, TrungTin Nguyen, Faicel Chamroukhi +1
Mixture of experts (MoE) models are widely applied for conditional probability density estimation problems. We demonstrate the richness of the class of MoE models by proving densen…
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…
Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces
TrungTin Nguyen, Faicel Chamroukhi, Hien D Nguyen +1
The class of location-scale finite mixtures is of enduring interest both from applied and theoretical perspectives of probability and statistics. We prove the following results: to…
Approximation by finite mixtures of continuous density functions that vanish at infinity
T Tin Nguyen, Hien D Nguyen, Faicel Chamroukhi +1
Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Un…