Phan, Hoang

13 publications

ICCV 2025 Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective Hoang Phan, Lam Tran, Quyen Tran, Ngoc Tran, Tuan Truong, Qi Lei, Nhat Ho, Dinh Phung, Trung Le

NeurIPS 2025 Hyperparameter Transfer Enables Consistent Gains of Matrix-Preconditioned Optimizers Across Scales Shikai Qiu, Zixi Chen, Hoang Phan, Qi Lei, Andrew Gordon Wilson

CVPRW 2025 PLVM: A Tuning-Free Approach for Personalized Large Vision-Language Model Chau Pham, Hoang Phan, David S. Doermann, Yunjie Tian

CVPR 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

NeurIPS 2025 Unveiling Concept Attribution in Diffusion Models Quang H Nguyen, Hoang Phan, Khoa D Doan

ICML 2024 Controllable Prompt Tuning for Balancing Group Distributional Robustness Hoang Phan, Andrew Gordon Wilson, Qi Lei

NeurIPS 2024 DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation Hao Phung, Quan Dao, Trung Dao, Hoang Phan, Dimitris N. Metaxas, Anh Tran

NeurIPS 2024 Enhancing Domain Adaptation Through Prompt Gradient Alignment Hoang Phan, Lam Tran, Quyen Tran, Trung Le

NeurIPSW 2024 Randomly Pivoted V-Optimal Design: Fast Data Selection Under Low Intrinsic Dimension Yijun Dong, Xiang Pan, Hoang Phan, Qi Lei

NeurIPS 2024 Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning Yijun Dong, Hoang Phan, Xiang Pan, Qi Lei

NeurIPS 2023 Flat Seeking Bayesian Neural Networks Van-Anh Nguyen, Tung-Long Vuong, Hoang Phan, Thanh-Toan Do, Dinh Phung, Trung Le

AISTATS 2023 Global-Local Regularization via Distributional Robustness Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Phung

NeurIPS 2022 Stochastic Multiple Target Sampling Gradient Descent Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung