most citedModel Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ML2026

Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models

TrungKhang Tran, TrungTin Nguyen, Md Abul Bashar +3

Mixture-of-Experts (MoE) architectures combine specialized predictors through a learned gate and are effective across regression and classification, but for classification with sof…

cs.LG2025

Sparse classification with positive-confidence data in high dimensions

The Tien Mai, Mai Anh Nguyen, Trung Nghia Nguyen

High-dimensional learning problems, where the number of features exceeds the sample size, often require sparse regularization for effective prediction and variable selection. While…

stat.ML20251 cited

Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures

Tuan Thai, TrungTin Nguyen, Dat Do +2

Mixture of Experts (MoE) models constitute a widely utilized class of ensemble learning approaches in statistics and machine learning, known for their flexibility and computational…

stat.ME2025

A Unified Framework for Variable Selection in Model-Based Clustering with Missing Not at Random

Binh H. Ho, Long Nguyen Chi, TrungTin Nguyen +3

Model-based clustering integrated with variable selection is a powerful tool for uncovering latent structures within complex data. However, its effectiveness is often hindered by c…

cs.LG2025

Near-Polynomially Competitive Active Logistic Regression

Yihan Zhou, Eric Price, Trung Nguyen

We address the problem of active logistic regression in the realizable setting. It is well known that active learning can require exponentially fewer label queries compared to pass…