Ho, Nhat

95 publications

AAAI 2025 Attack on Prompt: Backdoor Attack in Prompt-Based Continual Learning Trang Nguyen, Anh Tran, Nhat Ho

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 ExGra-Med: Extended Context Graph Alignment for Medical Vision-Language Models Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Hoang-Bao Le, Tai Nguyen, Anh-Tien Nguyen, TrungTin Nguyen, Nhat Ho, Pengtao Xie, Roger Wattenhofer, Daniel Sonntag, James Zou, Mathias Niepert

ICLRW 2025 Few-Shot Whole Slide Pathology Classification with Multi-Granular Vision-Language Models Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Nhat Ho, Jacqueline Michelle Metsch, Miriam Cindy Maurer, Daniel Sonntag, Hanibal Bohnenberger, Anne-Christin Hauschild

ICML 2025 Improving Generalization with Flat Hilbert Bayesian Inference Tuan Truong, Quyen Tran, Ngoc-Quan Pham, Nhat Ho, Dinh Phung, Trung Le

JMLR 2025 Instability, Computational Efficiency and Statistical Accuracy Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu

ICML 2025 Lightspeed Geometric Dataset Distance via Sliced Optimal Transport Khai Nguyen, Hai Nguyen, Tuan Pham, Nhat Ho

TMLR 2025 MGPATH: A Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot Whole Slide Pathology Classification Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep, Trung Quoc Nguyen, Nhat Ho, Jacqueline Michelle Metsch, Miriam Cindy Maurer, Daniel Sonntag, Hanibal Bohnenberger, Anne-Christin Hauschild

NeurIPS 2025 On Minimax Estimation of Parameters in SoftMax-Contaminated Mixture of Experts Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho, Alessandro Rinaldo

ICML 2025 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

ICML 2025 RepLoRA: Reparameterizing Low-Rank Adaptation via the Perspective of Mixture of Experts Tuan Truong, Chau Nguyen, Huy Nguyen, Minh Le, Trung Le, Nhat Ho

ICLR 2025 Revisiting Prefix-Tuning: Statistical Benefits of Reparameterization Among Prompts Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho

ICLR 2025 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

ICLR 2025 Towards Marginal Fairness Sliced Wasserstein Barycenter Khai Nguyen, Hai Nguyen, Nhat Ho

AISTATS 2025 Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho

ICLR 2025 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

NeurIPS 2024 A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings Disha Makhija, Joydeep Ghosh, Nhat Ho

ICML 2024 A General Theory for SoftMax Gating Multinomial Logistic Mixture of Experts Huy Nguyen, Pedram Akbarian, Trungtin Nguyen, Nhat Ho

NeurIPS 2024 Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization Nicola Bariletto, Nhat Ho

ICLR 2024 Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho

ICLR 2024 Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction Thanh Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie

NeurIPS 2024 FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria

NeurIPS 2024 Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions Khai Nguyen, Nhat Ho

ICML 2024 Improving Computational Complexity in Statistical Models with Local Curvature Information Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho

CVPR 2024 Integrating Efficient Optimal Transport and Functional Maps for Unsupervised Shape Correspondence Learning Tung Le, Khai Nguyen, Shanlin Sun, Nhat Ho, Xiaohui Xie

ICML 2024 Is Temperature Sample Efficient for SoftMax Gaussian Mixture of Experts? Huy Nguyen, Pedram Akbarian, Nhat Ho

ICMLW 2024 Marginal Fairness Sliced Wasserstein Barycenter Khai Nguyen, Hai Nguyen, Nhat Ho

NeurIPS 2024 Mixture of Experts Meets Prompt-Based Continual Learning Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho

ICML 2024 Neural Collapse for Cross-Entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho

ICML 2024 On Least Square Estimation in SoftMax Gating Mixture of Experts Huy Nguyen, Nhat Ho, Alessandro Rinaldo

AISTATS 2024 On Parameter Estimation in Deviated Gaussian Mixture of Experts Huy Nguyen, Khai Nguyen, Nhat Ho

JMLR 2024 On the Computational and Statistical Complexity of Over-Parameterized Matrix Sensing Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

ICLR 2024 Quasi-Monte Carlo for 3D Sliced Wasserstein Khai Nguyen, Nicola Bariletto, Nhat Ho

ICLR 2024 Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu

NeurIPS 2024 Sigmoid Gating Is More Sample Efficient than SoftMax Gating in Mixture of Experts Huy Nguyen, Nhat Ho, Alessandro Rinaldo

ICLR 2024 Sliced Wasserstein Estimation with Control Variates Khai Nguyen, Nhat Ho

ICML 2024 Sliced Wasserstein with Random-Path Projecting Directions Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho

ICLR 2024 Statistical Perspective of Top-K Sparse SoftMax Gating Mixture of Experts Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho

TMLR 2024 Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari

ICML 2024 Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An Thai Le, Trungtin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert

AISTATS 2024 Towards Convergence Rates for Parameter Estimation in Gaussian-Gated Mixture of Experts Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho

ICLR 2023 A Primal-Dual Framework for Transformers and Neural Networks Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard Baraniuk, Stanley Osher

NeurIPS 2023 Demystifying SoftMax Gating Function in Gaussian Mixture of Experts Huy Nguyen, TrungTin Nguyen, Nhat Ho

NeurIPS 2023 Designing Robust Transformers Using Robust Kernel Density Estimation Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho

NeurIPS 2023 Energy-Based Sliced Wasserstein Distance Khai Nguyen, Nhat Ho

ICMLW 2023 Fast Approximation of the Generalized Sliced-Wasserstein Distance Le Quang Dung, Huy Nguyen, Khai Nguyen, Nhat Ho

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

ICLR 2023 Hierarchical Sliced Wasserstein Distance Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen, Nhat Ho

AAAI 2023 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

NeurIPS 2023 LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-Order Graph Matching Duy M. H. Nguyen, Hoang Nguyen, Nghiem Diep, Tan Ngoc Pham, Tri Cao, Binh Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert

NeurIPS 2023 Markovian Sliced Wasserstein Distances: Beyond Independent Projections Khai Nguyen, Tongzheng Ren, Nhat Ho

NeurIPS 2023 Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models Dat Do, Huy Nguyen, Khai Nguyen, Nhat Ho

ICML 2023 Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data Hien Dang, Tho Tran Huu, Stanley Osher, Hung The Tran, Nhat Ho, Tan Minh Nguyen

ICML 2023 On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances Aritra Guha, Nhat Ho, Xuanlong Nguyen

NeurIPSW 2023 On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation Duy Minh Ho Nguyen, Tan Ngoc Pham, Nghiem Tuong Diep, Nghi Quoc Phan, Quang Pham, Vinh Tong, Binh T. Nguyen, Ngan Hoang Le, Nhat Ho, Pengtao Xie, Daniel Sonntag, Mathias Niepert

ICML 2023 Revisiting Over-Smoothing and Over-Squashing Using Ollivier-Ricci Curvature Khang Nguyen, Nong Minh Hieu, Vinh Duc Nguyen, Nhat Ho, Stanley Osher, Tan Minh Nguyen

ICML 2023 Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction Khai Nguyen, Dang Nguyen, Nhat Ho

NeurIPSW 2023 Sliced Wasserstein Estimation with Control Variates Khai Nguyen, Nhat Ho

AISTATS 2022 On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity Khang Le, Huy Nguyen, Khai Nguyen, Tung Pham, Nhat Ho

AISTATS 2022 On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms Nhat Ho, Tianyi Lin, Michael Jordan

AISTATS 2022 Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho

AISTATS 2022 Weak Separation in Mixture Models and Implications for Principal Stratification Nhat Ho, Avi Feller, Evan Greif, Luke Miratrix, Natesh Pillai

NeurIPS 2022 Amortized Projection Optimization for Sliced Wasserstein Generative Models Khai Nguyen, Nhat Ho

ICML 2022 Architecture Agnostic Federated Learning for Neural Networks Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh

NeurIPS 2022 Beyond Black Box Densities: Parameter Learning for the Deviated Components Dat Do, Nhat Ho, Xuanlong Nguyen

JMLR 2022 Convergence Rates for Gaussian Mixtures of Experts Nhat Ho, Chiao-Yu Yang, Michael I. Jordan

ICML 2022 Entropic Gromov-Wasserstein Between Gaussian Distributions Khang Le, Dung Q Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho

NeurIPS 2022 FourierFormer: Transformer Meets Generalized Fourier Integral Theorem Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley Osher, Nhat Ho

ICML 2022 Improving Mini-Batch Optimal Transport via Partial Transportation Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho

NeurIPS 2022 Improving Transformer with an Admixture of Attention Heads Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam, Minh Pham, Khuong Duy Nguyen, Nhat Ho, Stanley Osher

ICML 2022 Improving Transformers with Probabilistic Attention Keys Tam Minh Nguyen, Tan Minh Nguyen, Dung D. D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard Baraniuk, Nhat Ho, Stanley Osher

ICML 2022 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

JMLR 2022 On the Complexity of Approximating Multimarginal Optimal Transport Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan

JMLR 2022 On the Efficiency of Entropic Regularized Algorithms for Optimal Transport Tianyi Lin, Nhat Ho, Michael I. Jordan

ICML 2022 Refined Convergence Rates for Maximum Likelihood Estimation Under Finite Mixture Models Tudor Manole, Nhat Ho

NeurIPS 2022 Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution Khai Nguyen, Nhat Ho

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

AISTATS 2021 Flow-Based Alignment Approaches for Probability Measures in Different Spaces Tam Le, Nhat Ho, Makoto Yamada

AISTATS 2021 On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression Jeongyeol Kwon, Nhat Ho, Constantine Caramanis

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

ICLR 2021 Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui

ICML 2021 LAMDA: Label Matching Deep Domain Adaptation Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung

JMLR 2021 On Efficient Multilevel Clustering via Wasserstein Distances Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Phung

NeurIPS 2021 On Robust Optimal Transport: Computational Complexity and Barycenter Computation Khang Le, Huy Nguyen, Quang M Nguyen, Tung Pham, Hung Bui, Nhat Ho

ICCV 2021 Point-Set Distances for Learning Representations of 3D Point Clouds Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua

NeurIPS 2021 Structured Dropout Variational Inference for Bayesian Neural Networks Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui, Nhat Ho

AISTATS 2020 Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter Wenshuo Guo, Nhat Ho, Michael Jordan

NeurIPS 2020 Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan

ICML 2020 On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui

NeurIPS 2020 Projection Robust Wasserstein Distance and Riemannian Optimization Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan

AISTATS 2020 Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin Wainwright, Michael Jordan, Bin Yu

ICML 2019 On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms Tianyi Lin, Nhat Ho, Michael Jordan

AISTATS 2019 Probabilistic Multilevel Clustering via Composite Transportation Distance Nhat Ho, Viet Huynh, Dinh Phung, Michael Jordan

NeurIPS 2018 Theoretical Guarantees for EM Under Misspecified Gaussian Mixture Models Raaz Dwivedi, Nhật Hồ, Koulik Khamaru, Martin J. Wainwright, Michael I Jordan

ICML 2017 Multilevel Clustering via Wasserstein Means Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung