Anh Tuan Bui

According to our database, Anh Tuan Bui authored at least 26 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Adaptive Subspace Projection for Generative Personalization.

Van-Anh Nguyen, Anh Tuan Bui, Tamas Abraham, Junae Kim, Amardeep Kaur, Rollin Omari, Thuy-Trang Vu, Dinh Phung

CoRR, May, 2026

Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence.

Quoc Minh Nguyen, Trung Le, Jing Wu, Anh Tuan Bui, Mehrtash Harandi

CoRR, March, 2026

Improving LLM Unlearning Robustness via Random Perturbations.

Dang Huu-Tien, Hoang Thanh-Tung, Anh Tuan Bui, Nguyen Minh Phuong, Nguyen Minh Le, Naoya Inoue

Trans. Mach. Learn. Res., 2026

Scalable data twinning.

Sujay Mudalgi, Anh Tuan Bui

Pattern Recognit. Lett., 2026

Conditional multidimensional scaling with incomplete conditioning data.

Anh Tuan Bui

J. Multivar. Anal., 2026

2025

Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them.

Anh Tuan Bui, Thuy-Trang Vu, Long Tung Vuong, Trung Le, Paul Montague, Tamas Abraham, Junae Kim, Dinh Phung

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Root cause analysis of manufacturing variation from optical scanning data.

Anh Tuan Bui

Ann. Oper. Res., August, 2024

Dimension Reduction With Prior Information for Knowledge Discovery.

Anh Tuan Bui

IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

Connective Viewpoints of Signal-to-Noise Diffusion Models.

Khanh Doan, Long Tung Vuong, Tuan Nguyen, Anh Tuan Bui, Quyen Tran, Thanh-Toan Do, Dinh Phung, Trung Le

CoRR, 2024

Removing Undesirable Concepts in Text-to-Image Generative Models with Learnable Prompts.

Anh Tuan Bui, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, Dinh Q. Phung

CoRR, 2024

2023

Concept Drift Monitoring and Diagnostics of Supervised Learning Models via Score Vectors.

Kungang Zhang, Anh Tuan Bui, Daniel W. Apley

Technometrics, April, 2023

Generating Adversarial Examples with Task Oriented Multi-Objective Optimization.

Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung

Trans. Mach. Learn. Res., 2023

Robust Contrastive Learning With Theory Guarantee.

Ngoc N. Tran, Lam Tran, Hoang Phan, Anh Tuan Bui, Tung Pham, Toan Tran, Dinh Q. Phung, Trung Le

CoRR, 2023

Optimal Transport Model Distributional Robustness.

Van-Anh Nguyen, Trung Le, Anh Tuan Bui, Thanh-Toan Do, Dinh Q. Phung

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Global-Local Regularization Via Distributional Robustness.

Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Analyzing Nonparametric Part-to-Part Variation in Surface Point Cloud Data.

Anh Tuan Bui, Daniel W. Apley

Technometrics, 2022

A closed-form solution for conditional multidimensional scaling.

Anh Tuan Bui

Pattern Recognit. Lett., 2022

Robust monitoring of stochastic textured surfaces.

Anh Tuan Bui, Daniel W. Apley

Int. J. Prod. Res., 2022

Multiple Perturbation Attack: Attack Pixelwise Under Different $\ell_p$-norms For Better Adversarial Performance.

Ngoc N. Tran, Anh Tuan Bui, Dinh Q. Phung, Trung Le

CoRR, 2022

A Unified Wasserstein Distributional Robustness Framework for Adversarial Training.

Anh Tuan Bui, Trung Le, Quan Hung Tran, He Zhao, Dinh Q. Phung

Proceedings of the Tenth International Conference on Learning Representations, 2022

On Global-view Based Defense via Adversarial Attack and Defense Risk Guaranteed Bounds.

Trung Le, Anh Tuan Bui, Le Minh Tri Tue, He Zhao, Paul Montague, Quan Hung Tran, Dinh Q. Phung

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Conditional Manifold Learning.

Anh Tuan Bui

CoRR, 2021

2019

Projection-free kernel principal component analysis for denoising.

Anh Tuan Bui, Joon-Ku Im, Daniel W. Apley, George C. Runger

Neurocomputing, 2019

An exploratory analysis approach for understanding variation in stochastic textured surfaces.

Anh Tuan Bui, Daniel W. Apley

Comput. Stat. Data Anal., 2019

2018

A Monitoring and Diagnostic Approach for Stochastic Textured Surfaces.

Anh Tuan Bui, Daniel W. Apley

Technometrics, 2018

2012

Learning Bayesian network structure using Markov blanket decomposition.

Anh Tuan Bui, Chi-Hyuck Jun

Pattern Recognit. Lett., 2012