Hoang Phan

According to our database, Hoang Phan authored at least 20 papers between 2021 and 2025.

Collaborative distances:

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

2025

Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation.

Tung-Long Vuong, Hoang Phan, Vy Vo, Anh Bui, Thanh-Toan Do, Trung Le, Dinh Phung

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

PLVM: A tuning-free approach for Personalized Large Vision-Language Model.

Chau Pham, Hoang Phan, David S. Doermann, Yunjie Tian

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024

Personalized Large Vision-Language Models.

Chau Pham, Hoang Phan, David S. Doermann, Yunjie Tian

CoRR, 2024

Unveiling Concept Attribution in Diffusion Models.

Quang H. Nguyen, Hoang Phan, Khoa D. Doan

CoRR, 2024

DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation.

Hao Phung, Quan Dao, Trung Tuan Dao, Hoang Phan, Dimitris N. Metaxas, Anh Tuan Tran

CoRR, 2024

Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning.

Yijun Dong, Hoang Phan, Xiang Pan, Qi Lei

CoRR, 2024

Enhancing Domain Adaptation through Prompt Gradient Alignment.

Hoang Phan, Lam Tran, Quyen Tran, Trung Le

CoRR, 2024

Controllable Prompt Tuning For Balancing Group Distributional Robustness.

Hoang Phan, Andrew Gordon Wilson, Qi Lei

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Full High-Dimensional Intelligible Learning In 2-D Lossless Visualization Space.

Boris Kovalerchuk, Hoang Phan

CoRR, 2023

Sharpness & Shift-Aware Self-Supervised Learning.

Ngoc N. Tran, Son Duong, Hoang Phan, Tung Pham, Dinh Q. Phung, Trung Le

CoRR, 2023

Flat Seeking Bayesian Neural Networks.

Van-Anh Nguyen, Long Tung Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le

CoRR, 2023

Flat Seeking Bayesian Neural Networks.

Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Q. Phung, Trung Le

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

Continual Learning with Optimal Transport based Mixture Model.

Quyen Tran, Hoang Phan, Khoat Than, Dinh Q. Phung, Trung Le

CoRR, 2022

Improving Multi-task Learning via Seeking Task-based Flat Regions.

Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le

CoRR, 2022

Global-Local Regularization Via Distributional Robustness.

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

CoRR, 2022

Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation.

Hoang Phan, Anh Phan Tuan, Son Nguyen, Ngo Van Linh, Khoat Than

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Stochastic Multiple Target Sampling Gradient Descent.

Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Full interpretable machine learning in 2D with inline coordinates.

Boris Kovalerchuk, Hoang Phan

Proceedings of the 25th International Conference Information Visualisation, 2021