activity
20232026
most citedOn the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

4 citations · 6 across the 6 of their papers we have counts for

collaborators

7 papers

stat.ML2026

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…

stat.ML2025

Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency Without Model Sweeps

Do Tien Hai, Trung Nguyen Mai, TrungTin Nguyen +3

We develop a unified statistical framework for softmax-gated Gaussian mixture of experts (SGMoE) that addresses three long-standing obstacles in parameter estimation and model sele…

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.LG2024★ 1 cited

Accelerating Transformers with Spectrum-Preserving Token Merging

Hoai-Chau Tran, Duy M. H. Nguyen, Duy M. Nguyen +7

Increasing the throughput of the Transformer architecture, a foundational component used in numerous state-of-the-art models for vision and language tasks (e.g., GPT, LLaVa), is an…

cs.LG2024★ 1 cited

CompeteSMoE -- Effective Training of Sparse Mixture of Experts via Competition

Quang Pham, Giang Do, Huy Nguyen +8

Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width. However, effective traini…

cs.LG2023

HyperRouter: Towards Efficient Training and Inference of Sparse Mixture of Experts

Giang Do, Khiem Le, Quang Pham +7

By routing input tokens to only a few split experts, Sparse Mixture-of-Experts has enabled efficient training of large language models. Recent findings suggest that fixing the rout…

eess.IV2023★ 4 cited

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Duy Minh Ho Nguyen, Tan Ngoc Pham, Nghiem Tuong Diep +9

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundatio…