| 2025 | AAAI | Attack on Prompt: Backdoor Attack in Prompt-Based Continual Learning. | Trang Nguyen, Anh Tran, Nhat Ho |
| 2025 | AISTATS | Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts. | Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho |
| 2025 | ICCV | Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective. | Hoang Phan, Lam Tran, Quyen Tran, Ngoc N. Tran, Tuan Truong, Qi Lei, Nhat Ho, Dinh Q. Phung, Trung Le |
| 2025 | ICLR | X-Drive: Cross-modality Consistent Multi-Sensor Data Synthesis for Driving Scenarios. | Yichen Xie, Chenfeng Xu, Chensheng Peng, Shuqi Zhao, Nhat Ho, Alexander T. Pham, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan |
| 2025 | ICLR | Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts. | Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho |
| 2025 | ICLR | Statistical Advantages of Perturbing Cosine Router in Mixture of Experts. | Huy Nguyen, Pedram Akbarian, Huyen Trang Pham, Thien Trang Nguyen Vu, Shujian Zhang, Nhat Ho |
| 2025 | ICLR | Towards Marginal Fairness Sliced Wasserstein Barycenter. | Khai Nguyen, Hai Nguyen, Nhat Ho |
| 2025 | ICML | On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation. | Nghiem Tuong Diep, Huy Nguyen, Chau Nguyen, Minh Le, Duy Minh Ho Nguyen, Daniel Sonntag, Mathias Niepert, Nhat Ho |
| 2025 | ICML | Lightspeed Geometric Dataset Distance via Sliced Optimal Transport. | Khai Nguyen, Hai Nguyen, Tuan Pham, Nhat Ho |
| 2025 | ICML | RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts. | Tuan Truong, Chau Nguyen, Huy Nguyen, Minh Le, Trung Le, Nhat Ho |
| 2025 | ICML | Improving Generalization with Flat Hilbert Bayesian Inference. | Tuan Truong, Quyen Tran, Ngoc-Quan Pham, Nhat Ho, Dinh Phung, Trung Le |
| 2024 | AISTATS | On Parameter Estimation in Deviated Gaussian Mixture of Experts. | Huy Nguyen, Khai Nguyen, Nhat Ho |
| 2024 | AISTATS | Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. | Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho |
| 2024 | CVPR | Integrating Efficient Optimal Transport and Functional Maps for Unsupervised Shape Correspondence Learning. | Tung Le, Khai Nguyen, Shanlin Sun, Nhat Ho, Xiaohui Xie |
| 2024 | ICASSP | Fast Approximation of the Generalized Sliced-Wasserstein Distance. | Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho |
| 2024 | ICLR | Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders. | Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho |
| 2024 | ICLR | Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction. | Thanh-Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie |
| 2024 | ICLR | Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. | Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu |
| 2024 | ICLR | Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts. | Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho |
| 2024 | ICLR | Quasi-Monte Carlo for 3D Sliced Wasserstein. | Khai Nguyen, Nicola Bariletto, Nhat Ho |
| 2024 | ICLR | Sliced Wasserstein Estimation with Control Variates. | Khai Nguyen, Nhat Ho |
| 2024 | ICML | Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model. | Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho |
| 2024 | ICML | Improving Computational Complexity in Statistical Models with Local Curvature Information. | Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho |
| 2024 | ICML | Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts? | Huy Nguyen, Pedram Akbarian, Nhat Ho |
| 2024 | ICML | A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts. | Huy Nguyen, Pedram Akbarian, TrungTin Nguyen, Nhat Ho |
| 2024 | ICML | On Least Square Estimation in Softmax Gating Mixture of Experts. | Huy Nguyen, Nhat Ho, Alessandro Rinaldo |
| 2024 | ICML | Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. | Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert |
| 2024 | ICML | Sliced Wasserstein with Random-Path Projecting Directions. | Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho |
| 2023 | AAAI | Joint Self-Supervised Image-Volume Representation Learning with Intra-inter Contrastive Clustering. | Duy M. H. Nguyen, Hoang Nguyen, Truong Thanh Nhat Mai, Tri Cao, Binh T. Nguyen, Nhat Ho, Paul Swoboda, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag |
| 2023 | AISTATS | Global-Local Regularization Via Distributional Robustness. | Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung |
| 2023 | ICASSP | A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. | Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk |
| 2023 | ICASSP | On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. | Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho |
| 2023 | ICLR | A Primal-Dual Framework for Transformers and Neural Networks. | Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher |
| 2023 | ICLR | Hierarchical Sliced Wasserstein Distance. | Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho |
| 2023 | ICML | Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data. | Hien Dang, Tho Tran Huu, Stanley J. Osher, Hung Tran-The, Nhat Ho, Tan Minh Nguyen |
| 2023 | ICML | On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances. | Aritra Guha, Nhat Ho, XuanLong Nguyen |
| 2023 | ICML | Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature. | Khang Nguyen, Nong Minh Hieu, Vinh Duc Nguyen, Nhat Ho, Stanley J. Osher, Tan Minh Nguyen |
| 2023 | ICML | Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction. | Khai Nguyen, Dang Nguyen, Nhat Ho |
| 2022 | AISTATS | Weak Separation in Mixture Models and Implications for Principal Stratification. | Nhat Ho, Avi Feller, Evan Greif, Luke Miratrix, Natesh S. Pillai |
| 2022 | AISTATS | On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms. | Nhat Ho, Tianyi Lin, Michael I. Jordan |
| 2022 | AISTATS | On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. | Khang Le, Huy Nguyen, Khai Nguyen, Tung Pham, Nhat Ho |
| 2022 | AISTATS | Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. | Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho |
| 2022 | ICML | Entropic Gromov-Wasserstein between Gaussian Distributions. | Khang Le, Dung Q. Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho |
| 2022 | ICML | Architecture Agnostic Federated Learning for Neural Networks. | Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh |
| 2022 | ICML | Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models. | Tudor A. Manole, Nhat Ho |
| 2022 | ICML | Improving Transformers with Probabilistic Attention Keys. | Tam Minh Nguyen, Tan Minh Nguyen, Dung D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher |
| 2022 | ICML | On Transportation of Mini-batches: A Hierarchical Approach. | Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho |
| 2022 | ICML | Improving Mini-batch Optimal Transport via Partial Transportation. | Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho |
| 2021 | AISTATS | On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression. | Jeongyeol Kwon, Nhat Ho, Constantine Caramanis |
| 2021 | AISTATS | Flow-based Alignment Approaches for Probability Measures in Different Spaces. | Tam Le, Nhat Ho, Makoto Yamada |
| 2021 | ICCV | Point-set Distances for Learning Representations of 3D Point Clouds. | Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua |
| 2021 | ICLR | Distributional Sliced-Wasserstein and Applications to Generative Modeling. | Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui |
| 2021 | ICLR | Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein. | Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui |
| 2021 | ICML | LAMDA: Label Matching Deep Domain Adaptation. | Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung |
| 2020 | AISTATS | Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. | Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu |
| 2020 | AISTATS | Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter. | Wenshuo Guo, Nhat Ho, Michael I. Jordan |
| 2020 | ICML | On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm. | Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui |
| 2019 | AISTATS | Probabilistic Multilevel Clustering via Composite Transportation Distance. | Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan |
| 2019 | ICML | On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms. | Tianyi Lin, Nhat Ho, Michael I. Jordan |
| 2017 | ICML | Multilevel Clustering via Wasserstein Means. | Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung |