About

Welcome to my homepage! My full name is Huy Minh Nguyen, and I am currently a second-year Ph.D student at the Department of Statistics and Data Sciecnes, University of Texas at Austin where I am fortunate to be advised by Professor Nhat Ho and Professor Alessandro Rinaldo. Before that, I graduated from Ho Chi Minh City University of Science with a Bachelor’s degree in Mathematics (Summa Cum Laude).

Email: huynm@utexas.edu

Research Interests

My current research focuses on theoretical foundations for Mixture-of-Experts models. In particular, I try to comprehend the effects of various gating functions (namely softmax gate, top-K sparse softmax gate, dense-to-sparse gate, etc) on the convergence of density estimation and parameter estimation under the Mixture-of-Experts models. Based on insights from these results, I aim to design novel gating functions which help improve the performance of Mixture-of-Experts applications, including Large Language Models. Additionally, I am also interested in Optimal Transport theory.

(*) denotes equal contribution.

Selected Preprints

Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts

Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
Under review [arXiv]

A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts

Huy Nguyen, Pedram Akbarian, TrungTin Nguyen, Nhat Ho
Under review [arXiv]

Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts

Huy Nguyen*, TrungTin Nguyen*, Khai Nguyen, Nhat Ho
Under review [arXiv]

On Parameter Estimation in Deviated Gaussian Mixture of Experts

Huy Nguyen, Khai Nguyen, Nhat Ho
Under review

Selected Publications

Demystifying Softmax Gating Function in Gaussian Mixture of Experts

Huy Nguyen, TrungTin Nguyen, Nhat Ho
37th Conference on Neural Information Processing Systems (NeurIPS 2023) Spotlight [arXiv]

Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models

Dat Do*, Huy Nguyen*, Khai Nguyen, Nhat Ho
37th Conference on Neural Information Processing Systems (NeurIPS 2023) [arXiv]

Entropic Gromov-Wasserstein between Gaussian Distributions

Huy Nguyen*, Khang Le*, Dung Le*, Dat Do, Tung Pham, Nhat Ho
39th International Conference on Machine Learning (ICML 2022) [arXiv] [ICML]

On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity

Huy Nguyen*, Khang Le*, Khai Nguyen, Tung Pham, Nhat Ho
25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) [arXiv] [AISTATS]

On Robust Optimal Transport: Computational Complexity and Barycenter Computation

Huy Nguyen*, Khang Le*, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho
35th Conference on Neural Information Processing Systems (NeurIPS 2021) [arXiv] [NeurIPS]

Recent News

Professional Services

Conference Review: ICML (2022), NeurIPS (2022-2023), AISTATS (2022-2024) and ICLR (2024). Workshop Review: Frontier4LCD (ICML 2023).