Nhat Ho

212 papers A* 66A 13Misc 3Journal 130
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Statistical Theory of Gated Attention through the Lens of Hierarchical Mixture of Experts.
CoRR
Viet Nguyen, Tuan Minh Pham, Thinh Cao, Tan Dinh, Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2026 J jnl
Convergence Rates for Softmax Gating Mixture of Experts.
IEEE Trans. Inf. Theory
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2026 J jnl
Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models.
CoRR
TrungKhang Tran, TrungTin Nguyen, Md. Abul Bashar, Nhat Ho, Richi Nayak, Christopher C. Drovandi
2026 J jnl
Improving Minimax Estimation Rates for Contaminated Mixture of Multinomial Logistic Experts via Expert Heterogeneity.
CoRR
Fanqi Yan, Dung Le, Trang Pham, Huy Nguyen, Nhat Ho
2026 J jnl
Rethinking Multinomial Logistic Mixture of Experts with Sigmoid Gating Function.
CoRR
Tuan Minh Pham, Thinh Cao, Viet Nguyen, Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2025 J jnl
Adaptive Prompt: Unlocking the Power of Visual Prompt Tuning.
CoRR
Minh Le, Anh Nguyen, Huy Nguyen, Chau Nguyen, Nhat Ho
2025 A* conf
Attack on Prompt: Backdoor Attack in Prompt-Based Continual Learning.
AAAI
Trang Nguyen, Anh Tran, Nhat Ho
2025 J jnl
CompeteSMoE - Statistically Guaranteed Mixture of Experts Training via Competition.
CoRR
Nam V. Nguyen, Huy Nguyen, Quang Pham, Van Nguyen, Savitha Ramasamy, Nhat Ho
2025 J jnl
Convergence Rates for Softmax Gating Mixture of Experts.
CoRR
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2025 J jnl
Dendrograms of Mixing Measures for Softmax-Gated Gaussian Mixture of Experts: Consistency without Model Sweeps.
CoRR
Do Tien Hai, Trung Nguyen Mai, TrungTin Nguyen, Nhat Ho, Binh T. Nguyen, Christopher C. Drovandi
2025 J jnl
DoRAN: Stabilizing Weight-Decomposed Low-Rank Adaptation via Noise Injection and Auxiliary Networks.
CoRR
Nghiem Tuong Diep, Hien Dang, Tuan Truong, Tan Dinh, Huy Nguyen, Nhat Ho
2025 J jnl
Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances.
CoRR
Khai Nguyen, Hai Nguyen, Nhat Ho
2025 J jnl
HoRA: Cross-Head Low-Rank Adaptation with Joint Hypernetworks.
CoRR
Nghiem Tuong Diep, Dung Le, Tuan Truong, Tan Dinh, Huy Nguyen, Nhat Ho
2025 A* conf
Improving Generalization with Flat Hilbert Bayesian Inference.
ICML
Tuan Truong, Quyen Tran, Ngoc-Quan Pham, Nhat Ho, Dinh Phung, Trung Le
2025 J jnl
Instability, Computational Efficiency and Statistical Accuracy.
J. Mach. Learn. Res.
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2025 A* conf
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport.
ICML
Khai Nguyen, Hai Nguyen, Tuan Pham, Nhat Ho
2025 J jnl
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport.
CoRR
Khai Nguyen, Hai Nguyen, Tuan Pham, Nhat Ho
2025 J jnl
MGPATH: A Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot Whole Slide Pathology Classification.
Trans. Mach. Learn. Res.
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
2025 J jnl
MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification.
CoRR
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
2025 J jnl
Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures.
CoRR
Tuan Thai, TrungTin Nguyen, Dat Do, Nhat Ho, Christopher C. Drovandi
2025 J jnl
On DeepSeekMoE: Statistical Benefits of Shared Experts and Normalized Sigmoid Gating.
CoRR
Huy Nguyen, Thong T. Doan, Quang Pham, Nghi D. Q. Bui, Nhat Ho, Alessandro Rinaldo
2025 J jnl
On Minimax Estimation of Parameters in Softmax-Contaminated Mixture of Experts.
CoRR
Fanqi Yan, Huy Nguyen, Dung Le, Pedram Akbarian, Nhat Ho, Alessandro Rinaldo
2025 A* conf
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation.
ICML
Nghiem Tuong Diep, Huy Nguyen, Chau Nguyen, Minh Le, Duy Minh Ho Nguyen, Daniel Sonntag, Mathias Niepert, Nhat Ho
2025 J jnl
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation.
CoRR
Nghiem Tuong Diep, Huy Nguyen, Chau Nguyen, Minh Le, Duy M. H. Nguyen, Daniel Sonntag, Mathias Niepert, Nhat Ho
2025 J jnl
One-Prompt Strikes Back: Sparse Mixture of Experts for Prompt-based Continual Learning.
CoRR
Minh Le, Bao-Ngoc Dao, Huy Nguyen, Quyen Tran, Anh Nguyen, Nhat Ho
2025 J jnl
RepLoRA: Reparameterizing Low-Rank Adaptation via the Perspective of Mixture of Experts.
CoRR
Tuan Truong, Chau Nguyen, Huy Nguyen, Le Minh Nguyen, Trung Le, Nhat Ho
2025 A* conf
RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts.
ICML
Tuan Truong, Chau Nguyen, Huy Nguyen, Minh Le, Trung Le, Nhat Ho
2025 A* conf
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts.
ICLR
Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho
2025 J jnl
S-Chain: Structured Visual Chain-of-Thought For Medicine.
CoRR
Khai Le-Duc, Duy M. H. Nguyen, Phuong T. H. Trinh, Tien-Phat Nguyen, Nghiem Tuong Diep, An Ngo, Tung Vu, Trinh Vuong, Anh-Tien Nguyen, Mau Nguyen, Van Trung Hoang, Khai-Nguyen Nguyen, Hy Nguyen, Chris Ngo, Anji Liu, Nhat Ho, Anne-Christin Hauschild, Khanh Xuan Nguyen, Thanh Nguyen-Tang, Pengtao Xie, Daniel Sonntag, James Zou, Mathias Niepert, Anh Totti Nguyen
2025 J jnl
Shape-Adapting Gated Experts: Dynamic Expert Routing for Colonoscopic Lesion Segmentation.
CoRR
Gia Huy Thai, Hoang-Nguyen Vu, Anh-Minh Phan, Quang-Thinh Ly, Tram Dinh, Thi-Ngoc-Truc Nguyen, Nhat Ho
2025 J jnl
Sigmoid Self-Attention is Better than Softmax Self-Attention: A Mixture-of-Experts Perspective.
CoRR
Fanqi Yan, Huy Nguyen, Pedram Akbarian, Nhat Ho, Alessandro Rinaldo
2025 A* conf
Statistical Advantages of Perturbing Cosine Router in Mixture of Experts.
ICLR
Huy Nguyen, Pedram Akbarian, Huyen Trang Pham, Thien Trang Nguyen Vu, Shujian Zhang, Nhat Ho
2025 A* conf
Towards Marginal Fairness Sliced Wasserstein Barycenter.
ICLR
Khai Nguyen, Hai Nguyen, Nhat Ho
2025 A conf
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts.
AISTATS
Fanqi Yan, Huy Nguyen, Le Quang Dung, Pedram Akbarian, Nhat Ho
2025 A* conf
X-Drive: Cross-modality Consistent Multi-Sensor Data Synthesis for Driving Scenarios.
ICLR
Yichen Xie, Chenfeng Xu, Chensheng Peng, Shuqi Zhao, Nhat Ho, Alexander T. Pham, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan
2024 A* conf
A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings.
NeurIPS
Disha Makhija, Joydeep Ghosh, Nhat Ho
2024 J jnl
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters.
SIAM J. Math. Data Sci.
Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2024 A* conf
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts.
ICML
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen, Nhat Ho
2024 J jnl
A Primal-Dual Framework for Transformers and Neural Networks.
CoRR
Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2024 J jnl
Backdoor Attack in Prompt-Based Continual Learning.
CoRR
Trang Nguyen, Anh Tran, Nhat Ho
2024 A* conf
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization.
NeurIPS
Nicola Bariletto, Nhat Ho
2024 J jnl
Bayesian Nonparametrics Meets Data-Driven Robust Optimization.
CoRR
Nicola Bariletto, Nhat Ho
2024 A* conf
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders.
ICLR
Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
2024 J jnl
Borrowing Strength in Distributionally Robust Optimization via Hierarchical Dirichlet Processes.
CoRR
Nicola Bariletto, Khai Nguyen, Nhat Ho
2024 J jnl
CompeteSMoE - Effective Training of Sparse Mixture of Experts via Competition.
CoRR
Quang Pham, Giang Do, Huy Nguyen, TrungTin Nguyen, Chenghao Liu, Mina Sartipi, Binh T. Nguyen, Savitha Ramasamy, Xiaoli Li, Steven C. H. Hoi, Nhat Ho
2024 A* conf
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction.
ICLR
Thanh-Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie
2024 Misc conf
Fast Approximation of the Generalized Sliced-Wasserstein Distance.
ICASSP
Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho
2024 A* conf
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion.
NeurIPS
Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria
2024 J jnl
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion.
CoRR
Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria
2024 J jnl
Global Optimality of the EM Algorithm for Mixtures of Two-Component Linear Regressions.
IEEE Trans. Inf. Theory
Jeongyeol Kwon, Wei Qian, Yudong Chen, Constantine Caramanis, Damek Davis, Nhat Ho
2024 A* conf
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions.
NeurIPS
Khai Nguyen, Nhat Ho
2024 J jnl
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions.
CoRR
Khai Nguyen, Nhat Ho
2024 A* conf
Improving Computational Complexity in Statistical Models with Local Curvature Information.
ICML
Pedram Akbarian, Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
2024 J jnl
Improving Generalization with Flat Hilbert Bayesian Inference.
CoRR
Tuan Truong, Quyen Tran, Quan Pham-Ngoc, Nhat Ho, Dinh Phung, Trung Le
2024 J jnl
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning.
CoRR
Tung Le, Khai Nguyen, Shanlin Sun, Nhat Ho, Xiaohui Xie
2024 A* conf
Integrating Efficient Optimal Transport and Functional Maps for Unsupervised Shape Correspondence Learning.
CVPR
Tung Le, Khai Nguyen, Shanlin Sun, Nhat Ho, Xiaohui Xie
2024 A* conf
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
ICML
Huy Nguyen, Pedram Akbarian, Nhat Ho
2024 J jnl
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts?
CoRR
Huy Nguyen, Pedram Akbarian, Nhat Ho
2024 J jnl
Leveraging Hierarchical Taxonomies in Prompt-based Continual Learning.
CoRR
Quyen Tran, Minh Le, Tuan Truong, Dinh Phung, Linh Ngo Van, Thien Huu Nguyen, Nhat Ho, Trung Le
2024 J jnl
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model.
CoRR
Duy M. H. Nguyen, Nghiem Tuong Diep, Trung Q. Nguyen, Hoang-Bao Le, Tai Nguyen, Tien Nguyen, TrungTin Nguyen, Nhat Ho, Pengtao Xie, Roger Wattenhofer, James Zhou, Daniel Sonntag, Mathias Niepert
2024 J jnl
Marginal Fairness Sliced Wasserstein Barycenter.
CoRR
Khai Nguyen, Hai Nguyen, Nhat Ho
2024 A* conf
Mixture of Experts Meets Prompt-Based Continual Learning.
NeurIPS
Minh Le, An Nguyen The, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Ngo Van, Nhat Ho
2024 J jnl
Mixture of Experts Meets Prompt-Based Continual Learning.
CoRR
Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho
2024 J jnl
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Feature Model.
CoRR
Hien Dang, Tho Tran, Tan Nguyen, Nhat Ho
2024 A* conf
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model.
ICML
Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
2024 J jnl
On Barycenter Computation: Semi-Unbalanced Optimal Transport-based Method on Gaussians.
CoRR
Ngoc-Hai Nguyen, Dung Le, Hoang-Phi Nguyen, Tung Pham, Nhat Ho
2024 J jnl
On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions.
CoRR
Huy Nguyen, Xing Han, Carl Harris, Suchi Saria, Nhat Ho
2024 A* conf
On Least Square Estimation in Softmax Gating Mixture of Experts.
ICML
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2024 J jnl
On Least Squares Estimation in Softmax Gating Mixture of Experts.
CoRR
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2024 A conf
On Parameter Estimation in Deviated Gaussian Mixture of Experts.
AISTATS
Huy Nguyen, Khai Nguyen, Nhat Ho
2024 J jnl
On Parameter Estimation in Deviated Gaussian Mixture of Experts.
CoRR
Huy Nguyen, Khai Nguyen, Nhat Ho
2024 J jnl
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing.
J. Mach. Learn. Res.
Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
2024 J jnl
Quadratic Gating Functions in Mixture of Experts: A Statistical Insight.
CoRR
Pedram Akbarian, Huy Nguyen, Xing Han, Nhat Ho
2024 A* conf
Quasi-Monte Carlo for 3D Sliced Wasserstein.
ICLR
Khai Nguyen, Nicola Bariletto, Nhat Ho
2024 A* conf
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation.
ICLR
Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Phung, Lizhen Qu
2024 J jnl
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation.
CoRR
Manh Luong, Khai Nguyen, Nhat Ho, Gholamreza Haffari, Dinh Q. Phung, Lizhen Qu
2024 J jnl
Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts.
CoRR
Minh Le, Chau Nguyen, Huy Nguyen, Quyen Tran, Trung Le, Nhat Ho
2024 A* conf
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts.
NeurIPS
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2024 J jnl
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts.
CoRR
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
2024 A* conf
Sliced Wasserstein Estimation with Control Variates.
ICLR
Khai Nguyen, Nhat Ho
2024 A* conf
Sliced Wasserstein with Random-Path Projecting Directions.
ICML
Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho
2024 J jnl
Sliced Wasserstein with Random-Path Projecting Directions.
CoRR
Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho
2024 J jnl
Statistical Advantages of Perturbing Cosine Router in Sparse Mixture of Experts.
CoRR
Huy Nguyen, Pedram Akbarian, Trang Pham, Trang Nguyen, Shujian Zhang, Nhat Ho
2024 A* conf
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts.
ICLR
Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
2024 J jnl
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models.
Trans. Mach. Learn. Res.
Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari
2024 A* conf
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks.
ICML
Duy Minh Ho Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
2024 J jnl
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks.
CoRR
Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
2024 A conf
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts.
AISTATS
Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho
2024 J jnl
Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts.
CoRR
Fanqi Yan, Huy Nguyen, Dung Le, Pedram Akbarian, Nhat Ho
2024 J jnl
X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios.
CoRR
Yichen Xie, Chenfeng Xu, Chensheng Peng, Shuqi Zhao, Nhat Ho, Alexander T. Pham, Mingyu Ding, Masayoshi Tomizuka, Wei Zhan
2023 J jnl
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts.
CoRR
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen, Nhat Ho
2023 A* conf
A Primal-Dual Framework for Transformers and Neural Networks.
ICLR
Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2023 Misc conf
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys.
ICASSP
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 J jnl
Control Variate Sliced Wasserstein Estimators.
CoRR
Khai Nguyen, Nhat Ho
2023 A* conf
Demystifying Softmax Gating Function in Gaussian Mixture of Experts.
NeurIPS
Huy Nguyen, TrungTin Nguyen, Nhat Ho
2023 J jnl
Demystifying Softmax Gating in Gaussian Mixture of Experts.
CoRR
Huy Nguyen, TrungTin Nguyen, Nhat Ho
2023 A* conf
Designing Robust Transformers using Robust Kernel Density Estimation.
NeurIPS
Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
2023 J jnl
Diffeomorphic Deformation via Sliced Wasserstein Distance Optimization for Cortical Surface Reconstruction.
CoRR
Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie
2023 A* conf
Energy-Based Sliced Wasserstein Distance.
NeurIPS
Khai Nguyen, Nhat Ho
2023 J jnl
Energy-Based Sliced Wasserstein Distance.
CoRR
Khai Nguyen, Nhat Ho
2023 A conf
Global-Local Regularization Via Distributional Robustness.
AISTATS
Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung
2023 A* conf
Hierarchical Sliced Wasserstein Distance.
ICLR
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho
2023 A* conf
Joint Self-Supervised Image-Volume Representation Learning with Intra-inter Contrastive Clustering.
AAAI
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 A* conf
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching.
NeurIPS
Duy M. H. Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
2023 J jnl
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching.
CoRR
Duy M. H. Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
2023 A* conf
Markovian Sliced Wasserstein Distances: Beyond Independent Projections.
NeurIPS
Khai Nguyen, Tongzheng Ren, Nhat Ho
2023 J jnl
Markovian Sliced Wasserstein Distances: Beyond Independent Projections.
CoRR
Khai Nguyen, Tongzheng Ren, Nhat Ho
2023 A* conf
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models.
NeurIPS
Dat Do, Huy Nguyen, Khai Nguyen, Nhat Ho
2023 A* conf
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data.
ICML
Hien Dang, Tho Tran Huu, Stanley J. Osher, Hung Tran-The, Nhat Ho, Tan Minh Nguyen
2023 J jnl
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data.
CoRR
Hien Dang, Tho Tran, Tan M. Nguyen, Stanley J. Osher, Hung Tran-The, Nhat Ho
2023 Misc conf
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks.
ICASSP
Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho
2023 A* conf
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances.
ICML
Aritra Guha, Nhat Ho, XuanLong Nguyen
2023 J jnl
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation.
CoRR
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
2023 J jnl
Posterior Collapse in Linear Conditional and Hierarchical Variational Autoencoders.
CoRR
Hien Dang, Tho Tran, Tan Nguyen, Nhat Ho
2023 J jnl
Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings.
CoRR
Disha Makhija, Joydeep Ghosh, Nhat Ho
2023 J jnl
Quasi-Monte Carlo for 3D Sliced Wasserstein.
CoRR
Khai Nguyen, Nicola Bariletto, Nhat Ho
2023 A* conf
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature.
ICML
Khang Nguyen, Nong Minh Hieu, Vinh Duc Nguyen, Nhat Ho, Stanley J. Osher, Tan Minh Nguyen
2023 A* conf
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction.
ICML
Khai Nguyen, Dang Nguyen, Nhat Ho
2023 J jnl
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction.
CoRR
Khai Nguyen, Dang Nguyen, Nhat Ho
2023 J jnl
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts.
CoRR
Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
2023 J jnl
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts.
CoRR
Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho
2022 A* conf
Amortized Projection Optimization for Sliced Wasserstein Generative Models.
NeurIPS
Khai Nguyen, Nhat Ho
2022 J jnl
Amortized Projection Optimization for Sliced Wasserstein Generative Models.
CoRR
Khai Nguyen, Nhat Ho
2022 J jnl
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models.
CoRR
Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel A. Ward
2022 A* conf
Architecture Agnostic Federated Learning for Neural Networks.
ICML
Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
2022 J jnl
Architecture Agnostic Federated Learning for Neural Networks.
CoRR
Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
2022 J jnl
Beyond Black Box Densities: Parameter Learning for the Deviated Components.
CoRR
Dat Do, Nhat Ho, XuanLong Nguyen
2022 J jnl
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures.
CoRR
Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho
2022 A* conf
Beyond black box densities: Parameter learning for the deviated components.
NeurIPS
Dat Do, Nhat Ho, XuanLong Nguyen
2022 J jnl
Convergence Rates for Gaussian Mixtures of Experts.
J. Mach. Learn. Res.
Nhat Ho, Chiao-Yu Yang, Michael I. Jordan
2022 J jnl
Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering.
CoRR
Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho
2022 A* conf
Entropic Gromov-Wasserstein between Gaussian Distributions.
ICML
Khang Le, Dung Q. Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho
2022 J jnl
Fast Approximation of the Generalized Sliced-Wasserstein Distance.
CoRR
Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho
2022 J jnl
Federated Self-supervised Learning for Heterogeneous Clients.
CoRR
Disha Makhija, Nhat Ho, Joydeep Ghosh
2022 A* conf
FourierFormer: Transformer Meets Generalized Fourier Integral Theorem.
NeurIPS
Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley J. Osher, Nhat Ho
2022 J jnl
Global-Local Regularization Via Distributional Robustness.
CoRR
Hoang Phan, Trung Le, Trung Phung, Tuan-Anh Bui, Nhat Ho, Dinh Q. Phung
2022 J jnl
Hierarchical Sliced Wasserstein Distance.
CoRR
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho
2022 J jnl
Improving Computational Complexity in Statistical Models with Second-Order Information.
CoRR
Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
2022 J jnl
Improving Generative Flow Networks with Path Regularization.
CoRR
Anh Do, Duy Dinh, Tan M. Nguyen, Khuong Nguyen, Stanley J. Osher, Nhat Ho
2022 A* conf
Improving Mini-batch Optimal Transport via Partial Transportation.
ICML
Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho
2022 J jnl
Improving Multi-task Learning via Seeking Task-based Flat Regions.
CoRR
Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le
2022 A* conf
Improving Transformer with an Admixture of Attention Heads.
NeurIPS
Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam, Minh Pham, Duy Khuong Nguyen, Nhat Ho, Stanley J. Osher
2022 A* conf
Improving Transformers with Probabilistic Attention Keys.
ICML
Tam Minh Nguyen, Tan Minh Nguyen, Dung D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
2022 J jnl
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering.
CoRR
Duy M. H. Nguyen, Hoang Nguyen, Mai Thanh Nhat Truong, Tri Cao, Binh T. Nguyen, Nhat Ho, Paul Swoboda, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag
2022 A conf
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity.
AISTATS
Khang Le, Huy Nguyen, Khai Nguyen, Tung Pham, Nhat Ho
2022 A conf
On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms.
AISTATS
Nhat Ho, Tianyi Lin, Michael I. Jordan
2022 A* conf
On Transportation of Mini-batches: A Hierarchical Approach.
ICML
Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho
2022 J jnl
On the Complexity of Approximating Multimarginal Optimal Transport.
J. Mach. Learn. Res.
Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan
2022 J jnl
On the Efficiency of Entropic Regularized Algorithms for Optimal Transport.
J. Mach. Learn. Res.
Tianyi Lin, Nhat Ho, Michael I. Jordan
2022 A* conf
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models.
ICML
Tudor A. Manole, Nhat Ho
2022 J jnl
Revisiting Over-smoothing and Over-squashing using Ollivier's Ricci Curvature.
CoRR
Khang Nguyen, Tan Nguyen, Nhat Ho, Khuong Nguyen, Hieu Nong, Vinh Nguyen
2022 A* conf
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution.
NeurIPS
Khai Nguyen, Nhat Ho
2022 J jnl
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution.
CoRR
Khai Nguyen, Nhat Ho
2022 J jnl
Robustify Transformers with Robust Kernel Density Estimation.
CoRR
Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
2022 A* conf
Stochastic Multiple Target Sampling Gradient Descent.
NeurIPS
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
2022 J jnl
Stochastic Multiple Target Sampling Gradient Descent.
CoRR
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
2022 A conf
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent.
AISTATS
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
2022 J jnl
Transformer with Fourier Integral Attentions.
CoRR
Tan M. Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley J. Osher, Nhat Ho
2022 A conf
Weak Separation in Mixture Models and Implications for Principal Stratification.
AISTATS
Nhat Ho, Avi Feller, Evan Greif, Luke Miratrix, Natesh S. Pillai
2021 J jnl
An Efficient Mini-batch Method via Partial Transportation.
CoRR
Khai Nguyen, Dang Nguyen, Tung Pham, Nhat Ho
2021 J jnl
BoMb-OT: On Batch of Mini-batches Optimal Transport.
CoRR
Khai Nguyen, Quoc Nguyen, Nhat Ho, Tung Pham, Hung Bui, Dinh Phung, Trung Le
2021 A* conf
Distributional Sliced-Wasserstein and Applications to Generative Modeling.
ICLR
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021 J jnl
Entropic Gromov-Wasserstein between Gaussian Distributions.
CoRR
Khang Le, Dung Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho
2021 A conf
Flow-based Alignment Approaches for Probability Measures in Different Spaces.
AISTATS
Tam Le, Nhat Ho, Makoto Yamada
2021 J jnl
Improving Bayesian Inference in Deep Neural Networks with Variational Structured Dropout.
CoRR
Son Nguyen, Duong Nguyen, Khai Nguyen, Nhat Ho, Khoat Than, Hung Bui
2021 A* conf
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein.
ICLR
Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021 A* conf
LAMDA: Label Matching Deep Domain Adaptation.
ICML
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
2021 J jnl
Model Fusion of Heterogeneous Neural Networks via Cross-Layer Alignment.
CoRR
Dang Nguyen, Khai Nguyen, Dinh Phung, Hung Bui, Nhat Ho
2021 J jnl
On Label Shift in Domain Adaptation via Wasserstein Distance.
CoRR
Trung Le, Dat Do, Tuan Nguyen, Huy Nguyen, Hung Bui, Nhat Ho, Dinh Q. Phung
2021 J jnl
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity.
CoRR
Khang Le, Huy Nguyen, Tung Pham, Nhat Ho
2021 A* conf
On Robust Optimal Transport: Computational Complexity and Barycenter Computation.
NeurIPS
Khang Le, Huy Nguyen, Quang Minh Nguyen, Tung Pham, Hung Bui, Nhat Ho
2021 J jnl
On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation.
CoRR
Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui
2021 J jnl
On efficient multilevel Clustering via Wasserstein distances.
J. Mach. Learn. Res.
Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2021 A conf
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression.
AISTATS
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
2021 J jnl
On the computational and statistical complexity of over-parameterized matrix sensing.
CoRR
Jiacheng Zhuo, Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
2021 A* conf
Point-set Distances for Learning Representations of 3D Point Clouds.
ICCV
Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua
2021 J jnl
Point-set Distances for Learning Representations of 3D Point Clouds.
CoRR
Trung Nguyen, Quang-Hieu Pham, Tam Le, Tung Pham, Nhat Ho, Binh-Son Hua
2021 J jnl
Statistical Analysis from the Fourier Integral Theorem.
CoRR
Nhat Ho, Stephen G. Walker
2021 A* conf
Structured Dropout Variational Inference for Bayesian Neural Networks.
NeurIPS
Son Nguyen, Duong Nguyen, Khai Nguyen, Khoat Than, Hung Bui, Nhat Ho
2021 J jnl
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent.
CoRR
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
2021 J jnl
Transformer with a Mixture of Gaussian Keys.
CoRR
Tam Nguyen, Tan M. Nguyen, Dung Le, Khuong Nguyen, Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
2020 J jnl
Distributional Sliced-Wasserstein and Applications to Generative Modeling.
CoRR
Khai Nguyen, Nhat Ho, Tung Pham, Hung Bui
2020 A conf
Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter.
AISTATS
Wenshuo Guo, Nhat Ho, Michael I. Jordan
2020 A* conf
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm.
NeurIPS
Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan
2020 J jnl
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov Wasserstein.
CoRR
Khai Nguyen, Son Nguyen, Nhat Ho, Tung Pham, Hung Bui
2020 J jnl
Instability, Computational Efficiency and Statistical Accuracy.
CoRR
Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2020 A* conf
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm.
ICML
Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui
2020 J jnl
On Unbalanced Optimal Transport: An Analysis of Sinkhorn Algorithm.
CoRR
Khiem Pham, Khang Le, Nhat Ho, Tung Pham, Hung Bui
2020 J jnl
On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression.
CoRR
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
2020 A* conf
Projection Robust Wasserstein Distance and Riemannian Optimization.
NeurIPS
Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan
2020 J jnl
Projection Robust Wasserstein Distance and Riemannian Optimization.
CoRR
Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan
2020 J jnl
Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms.
CoRR
Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan
2020 A conf
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models.
AISTATS
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2019 J jnl
Accelerated Primal-Dual Coordinate Descent for Computational Optimal Transport.
CoRR
Wenshuo Guo, Nhat Ho, Michael I. Jordan
2019 J jnl
Challenges with EM in application to weakly identifiable mixture models.
CoRR
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu
2019 J jnl
Computationally Efficient Tree Variants of Gromov-Wasserstein.
CoRR
Tam Le, Nhat Ho, Makoto Yamada
2019 J jnl
Convergence Rates for Gaussian Mixtures of Experts.
CoRR
Nhat Ho, Chiao-Yu Yang, Michael I. Jordan
2019 J jnl
Global Error Bounds and Linear Convergence for Gradient-Based Algorithms for Trend Filtering and ๐“
CoRR
Nhat Ho, Tianyi Lin, Michael I. Jordan
2019 J jnl
On Efficient Multilevel Clustering via Wasserstein Distances.
CoRR
Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, Dinh Q. Phung
2019 A* conf
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms.
ICML
Tianyi Lin, Nhat Ho, Michael I. Jordan
2019 J jnl
On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms.
CoRR
Tianyi Lin, Nhat Ho, Michael I. Jordan
2019 J jnl
On Scalable Variant of Wasserstein Barycenter.
CoRR
Tam Le, Viet Huynh, Nhat Ho, Dinh Q. Phung, Makoto Yamada
2019 J jnl
On the Acceleration of the Sinkhorn and Greenkhorn Algorithms for Optimal Transport.
CoRR
Tianyi Lin, Nhat Ho, Michael I. Jordan
2019 J jnl
On the Complexity of Approximating Multimarginal Optimal Transport.
CoRR
Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan
2019 J jnl
Posterior Distribution for the Number of Clusters in Dirichlet Process Mixture Models.
CoRR
Chiao-Yu Yang, Nhat Ho, Michael I. Jordan
2019 A conf
Probabilistic Multilevel Clustering via Composite Transportation Distance.
AISTATS
Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
2019 J jnl
Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing.
CoRR
Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
2019 J jnl
Singularity Structures and Impacts on Parameter Estimation in Finite Mixtures of Distributions.
SIAM J. Math. Data Sci.
Nhat Ho, XuanLong Nguyen
2018 J jnl
Neural Rendering Model: Joint Generation and Prediction for Semi-Supervised Learning.
CoRR
Nhat Ho, Tan M. Nguyen, Ankit B. Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk
2018 J jnl
Probabilistic Multilevel Clustering via Composite Transportation Distance.
CoRR
Nhat Ho, Viet Huynh, Dinh Q. Phung, Michael I. Jordan
2018 A* conf
Theoretical guarantees for EM under misspecified Gaussian mixture models.
NeurIPS
Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan
2017 A* conf
Multilevel Clustering via Wasserstein Means.
ICML
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Q. Phung