Fast Support Vector Clustering. - Tung Pham 001; Trung Le 001; Thai Hoang Le; Dat Tran 001 (ESANN, 2016)

Scalable Support Vector Clustering Using Budget. - Tung Pham 001; Trung Le 001; Hang Dang (CoRR, 2017)

Fast support vector clustering. - Tung Pham 001; Hang Dang; Trung Le 001; Thai Hoang Le (Vietnam. J. Comput. Sci., 2017)

On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. - Khiem Pham; Khang Le; Nhat Ho; Tung Pham 001; Hung Bui 001 (ICML, 2020)

Point-set Distances for Learning Representations of 3D Point Clouds. - Trung Nguyen; Quang-Hieu Pham; Tam Le; Tung Pham 001; Nhat Ho; Binh-Son Hua (ICCV, 2021)

Distributional Sliced-Wasserstein and Applications to Generative Modeling. - Khai Nguyen; Nhat Ho; Tung Pham 001; Hung Bui 001 (ICLR, 2021)

Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. - Khai Nguyen; Son Nguyen; Nhat Ho; Tung Pham 001; Hung Bui 001 (ICLR, 2021)

On Robust Optimal Transport: Computational Complexity and Barycenter Computation. - Khang Le; Huy Nguyen; Quang Minh Nguyen; Tung Pham 001; Hung Bui 001; Nhat Ho (NeurIPS, 2021)

BoMb-OT: On Batch of Mini-batches Optimal Transport. - Khai Nguyen; Quoc Nguyen; Nhat Ho; Tung Pham 001; Hung Bui 001; Dinh Phung 001; Trung Le 001 (CoRR, 2021)

On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation. - Khang Le; Huy Nguyen; Quang Nguyen; Nhat Ho; Tung Pham 001; Hung Bui 001 (CoRR, 2021)

On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. - Khang Le; Huy Nguyen; Tung Pham 001; Nhat Ho (CoRR, 2021)

An Efficient Mini-batch Method via Partial Transportation. - Khai Nguyen; Dang Nguyen 002; Tung Pham 001; Nhat Ho (CoRR, 2021)

Entropic Gromov-Wasserstein between Gaussian Distributions. - Khang Le; Dung Le; Huy Nguyen; Dat Do; Tung Pham 001; Nhat Ho (CoRR, 2021)

On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. - Khang Le; Huy Nguyen; Khai Nguyen; Tung Pham 001; Nhat Ho (AISTATS, 2022)

Entropic Gromov-Wasserstein between Gaussian Distributions. - Khang Le; Dung Q. Le; Huy Nguyen; Dat Do; Tung Pham 001; Nhat Ho (ICML, 2022)

On Transportation of Mini-batches: A Hierarchical Approach. - Khai Nguyen; Dang Nguyen 002; Quoc Dinh Nguyen; Tung Pham 001; Hung Bui 001; Dinh Phung 001; Trung Le 001; Nhat Ho (ICML, 2022)

Improving Mini-batch Optimal Transport via Partial Transportation. - Khai Nguyen; Dang Nguyen 002; The-Anh Vu-Le; Tung Pham 001; Nhat Ho (ICML, 2022)

Sharpness & Shift-Aware Self-Supervised Learning. - Ngoc N. Tran; Son Duong; Hoang Phan; Tung Pham 001; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization. - Tuan Truong; Hoang-Phi Nguyen; Tung Pham 001; Minh-Tuan Tran; Mehrtash Harandi; Dinh Phung 001; Trung Le 001 (CoRR, 2023)

Robust Contrastive Learning With Theory Guarantee. - Ngoc N. Tran; Lam Tran; Hoang Phan; Anh Tuan Bui; Tung Pham 001; Toan Tran 003; Dinh Q. Phung; Trung Le 001 (CoRR, 2023)

COMBAT: Alternated Training for Effective Clean-Label Backdoor Attacks. - Tran Huynh; Dang Nguyen 002; Tung Pham 001; Anh Tran (AAAI, 2024)

Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization. - Haocheng Luo; Tuan Truong; Tung Pham 001; Mehrtash Harandi; Dinh Q. Phung; Trung Le 001 (NeurIPS, 2024)

Diversity-Aware Agnostic Ensemble of Sharpness Minimizers. - Anh Bui; Vy Vo; Tung Pham 001; Dinh Q. Phung; Trung Le 001 (CoRR, 2024)

On Barycenter Computation: Semi-Unbalanced Optimal Transport-based Method on Gaussians. - Ngoc-Hai Nguyen; Dung Le; Hoang-Phi Nguyen; Tung Pham 001; Nhat Ho (CoRR, 2024)

Low-Rank Adaptation in Multilinear Operator Networks for Security-Preserving Incremental Learning. - Huu Binh Ta; Duc Nguyen; Quyen Tran; Toan Tran 003; Tung Pham 001 (CVPR, 2025)