Nhat Ho

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 152

Top Venues

CoRR

NeurIPS

ICML

AISTATS

Publications

Khai Nguyen, Nicola Bariletto, Nhat Ho
Quasi-Monte Carlo for 3D Sliced Wasserstein. ICLR (2024)
Manh Luong, Khai Nguyen, Nhat Ho, Reza Haf, Dinh Phung, Lizhen Qu
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. ICLR (2024)
Huy Nguyen, Pedram Akbarian, Trang Pham, Trang Nguyen, Shujian Zhang, Nhat Ho
Statistical Advantages of Perturbing Cosine Router in Sparse Mixture of Experts. CoRR (2024)
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
On Least Squares Estimation in Softmax Gating Mixture of Experts. CoRR (2024)
Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. AISTATS (2024)
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
CompeteSMoE - Effective Training of Sparse Mixture of Experts via Competition. CoRR (2024)
Manh Luong, Khai Nguyen, Nhat Ho, Reza Haf, Dinh Q. Phung, Lizhen Qu
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation. CoRR (2024)
Huy Nguyen, Khai Nguyen, Nhat Ho
On Parameter Estimation in Deviated Gaussian Mixture of Experts. CoRR (2024)
Trang Nguyen, Anh Tran, Nhat Ho
Backdoor Attack in Prompt-Based Continual Learning. CoRR (2024)
Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari
Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models. Trans. Mach. Learn. Res. 2024 (2024)
Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho
Fast Approximation of the Generalized Sliced-Wasserstein Distance. ICASSP (2024)
Khai Nguyen, Nhat Ho
Sliced Wasserstein Estimation with Control Variates. ICLR (2024)
Huy Nguyen, Khai Nguyen, Nhat Ho
On Parameter Estimation in Deviated Gaussian Mixture of Experts. AISTATS (2024)
Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders. ICLR (2024)
Nicola Bariletto, Nhat Ho
Bayesian Nonparametrics Meets Data-Driven Robust Optimization. CoRR (2024)
Hien Dang, Tho Tran, Tan Nguyen, Nhat Ho
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Feature Model. CoRR (2024)
Khai Nguyen, Shujian Zhang, Tam Le, Nhat Ho
Sliced Wasserstein with Random-Path Projecting Directions. CoRR (2024)
Duy M. H. Nguyen, Nina Lukashina, Tai Nguyen, An T. Le, TrungTin Nguyen, Nhat Ho, Jan Peters, Daniel Sonntag, Viktor Zaverkin, Mathias Niepert
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks. CoRR (2024)
Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho
Mixture of Experts Meets Prompt-Based Continual Learning. CoRR (2024)
Tan M. Nguyen, Tam Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
A Primal-Dual Framework for Transformers and Neural Networks. CoRR (2024)
Huy Nguyen, Nhat Ho, Alessandro Rinaldo
Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts. CoRR (2024)
Thanh-Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction. ICLR (2024)
Tung Le, Khai Nguyen, Shanlin Sun, Nhat Ho, Xiaohui Xie
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning. CoRR (2024)
Khai Nguyen, Hai Nguyen, Nhat Ho
Marginal Fairness Sliced Wasserstein Barycenter. CoRR (2024)
Nicola Bariletto, Khai Nguyen, Nhat Ho
Borrowing Strength in Distributionally Robust Optimization via Hierarchical Dirichlet Processes. CoRR (2024)
Xing Han, Huy Nguyen, Carl Harris, Nhat Ho, Suchi Saria
FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusion. CoRR (2024)
Wenlong Mou, Nhat Ho, Martin J. Wainwright, Peter L. Bartlett, Michael I. Jordan
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters. SIAM J. Math. Data Sci. 6 (2) (2024)
Khai Nguyen, Nhat Ho
Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions. CoRR (2024)
Huy Nguyen, Pedram Akbarian, Nhat Ho
Is Temperature Sample Efficient for Softmax Gaussian Mixture of Experts? CoRR (2024)
Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts. ICLR (2024)
Huy Nguyen, TrungTin Nguyen, Nhat Ho
Demystifying Softmax Gating in Gaussian Mixture of Experts. CoRR (2023)
Khai Nguyen, Nhat Ho
Control Variate Sliced Wasserstein Estimators. CoRR (2023)
Khai Nguyen, Tongzheng Ren, Nhat Ho
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. NeurIPS (2023)
Disha Makhija, Joydeep Ghosh, Nhat Ho
Privacy Preserving Bayesian Federated Learning in Heterogeneous Settings. CoRR (2023)
Huy Nguyen, TrungTin Nguyen, Nhat Ho
Demystifying Softmax Gating Function in Gaussian Mixture of Experts. NeurIPS (2023)
Khai Nguyen, Dang Nguyen, Nhat Ho
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction. CoRR (2023)
Aritra Guha, Nhat Ho, XuanLong Nguyen
On Excess Mass Behavior in Gaussian Mixture Models with Orlicz-Wasserstein Distances. ICML (2023)
Huy Nguyen, Pedram Akbarian, TrungTin Nguyen, Nhat Ho
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts. CoRR (2023)
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
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching. NeurIPS (2023)
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
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP (2023)
Huy Nguyen, Pedram Akbarian, Fanqi Yan, Nhat Ho
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts. CoRR (2023)
Dang Nguyen, Trang Nguyen, Khai Nguyen, Dinh Q. Phung, Hung Hai Bui, Nhat Ho
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks. ICASSP (2023)
Hien Dang, Tho Tran Huu, Stanley J. Osher, Hung Tran-The, Nhat Ho, Tan Minh Nguyen
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data. ICML (2023)
Khai Nguyen, Tongzheng Ren, Nhat Ho
Markovian Sliced Wasserstein Distances: Beyond Independent Projections. CoRR (2023)
Khai Nguyen, Dang Nguyen, Nhat Ho
Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction. ICML (2023)
Duy M. H. Nguyen, Hoang Nguyen, Nghiem Diep, Tan N. Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching. CoRR (2023)
Khai Nguyen, Nhat Ho
Energy-Based Sliced Wasserstein Distance. NeurIPS (2023)
Hoang Phan, Trung Le, Trung Phung, Anh Tuan Bui, Nhat Ho, Dinh Q. Phung
Global-Local Regularization Via Distributional Robustness. AISTATS (2023)
Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
A Primal-Dual Framework for Transformers and Neural Networks. ICLR (2023)
Hien Dang, Tan Nguyen, Tho Tran, Hung Tran, Nhat Ho
Neural Collapse in Deep Linear Network: From Balanced to Imbalanced Data. CoRR (2023)
Hien Dang, Tho Tran, Tan Nguyen, Nhat Ho
Posterior Collapse in Linear Conditional and Hierarchical Variational Autoencoders. CoRR (2023)
Xing Han, Tongzheng Ren, Tan Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
Designing Robust Transformers using Robust Kernel Density Estimation. NeurIPS (2023)
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
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation. CoRR (2023)
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Minh Nguyen, Nhat Ho
Hierarchical Sliced Wasserstein Distance. ICLR (2023)
Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie
Diffeomorphic Deformation via Sliced Wasserstein Distance Optimization for Cortical Surface Reconstruction. CoRR (2023)
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
Joint Self-Supervised Image-Volume Representation Learning with Intra-inter Contrastive Clustering. AAAI (2023)
Khai Nguyen, Nhat Ho
Energy-Based Sliced Wasserstein Distance. CoRR (2023)
Huy Nguyen, TrungTin Nguyen, Khai Nguyen, Nhat Ho
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts. CoRR (2023)
Khang Nguyen, Nong Minh Hieu, Vinh Duc Nguyen, Nhat Ho, Stanley J. Osher, Tan Minh Nguyen
Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature. ICML (2023)
Khai Nguyen, Nicola Bariletto, Nhat Ho
Quasi-Monte Carlo for 3D Sliced Wasserstein. CoRR (2023)
Dat Do, Huy Nguyen, Khai Nguyen, Nhat Ho
Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models. NeurIPS (2023)
Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan
On the Complexity of Approximating Multimarginal Optimal Transport. J. Mach. Learn. Res. 23 (2022)
Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
Architecture Agnostic Federated Learning for Neural Networks. CoRR (2022)
Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley J. Osher, Nhat Ho
Transformer with Fourier Integral Attentions. CoRR (2022)
Nhat Ho, Avi Feller, Evan Greif, Luke Miratrix, Natesh S. Pillai
Weak Separation in Mixture Models and Implications for Principal Stratification. AISTATS (2022)
Khai Nguyen, Dang Nguyen, Quoc Dinh Nguyen, Tung Pham, Hung Bui, Dinh Phung, Trung Le, Nhat Ho
On Transportation of Mini-batches: A Hierarchical Approach. ICML (2022)
Khang Nguyen, Tan Nguyen, Nhat Ho, Khuong Nguyen, Hieu Nong, Vinh Nguyen
Revisiting Over-smoothing and Over-squashing using Ollivier's Ricci Curvature. CoRR (2022)
Tongzheng Ren, Fuheng Cui, Sujay Sanghavi, Nhat Ho
Beyond EM Algorithm on Over-specified Two-Component Location-Scale Gaussian Mixtures. CoRR (2022)
Tongzheng Ren, Fuheng Cui, Alexia Atsidakou, Sujay Sanghavi, Nhat Ho
Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent. AISTATS (2022)
Disha Makhija, Xing Han, Nhat Ho, Joydeep Ghosh
Architecture Agnostic Federated Learning for Neural Networks. ICML (2022)
Anh Do, Duy Dinh, Tan Nguyen, Khuong Nguyen, Stanley J. Osher, Nhat Ho
Improving Generative Flow Networks with Path Regularization. CoRR (2022)
Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho
Robustify Transformers with Robust Kernel Density Estimation. CoRR (2022)
Dung Le, Huy Nguyen, Khai Nguyen, Trang Nguyen, Nhat Ho
Fast Approximation of the Generalized Sliced-Wasserstein Distance. CoRR (2022)
Tongzheng Ren, Jiacheng Zhuo, Sujay Sanghavi, Nhat Ho
Improving Computational Complexity in Statistical Models with Second-Order Information. CoRR (2022)
Tianyi Lin, Nhat Ho, Michael I. Jordan
On the Efficiency of Entropic Regularized Algorithms for Optimal Transport. J. Mach. Learn. Res. 23 (2022)
Hoang Phan, Trung Le, Trung Phung, Tuan Anh Bui, Nhat Ho, Dinh Q. Phung
Global-Local Regularization Via Distributional Robustness. CoRR (2022)
Tan Nguyen, Minh Pham, Tam Nguyen, Khai Nguyen, Stanley J. Osher, Nhat Ho
FourierFormer: Transformer Meets Generalized Fourier Integral Theorem. NeurIPS (2022)
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Stochastic Multiple Target Sampling Gradient Descent. CoRR (2022)
Hoang Phan, Lam Tran, Ngoc N. Tran, Nhat Ho, Dinh Q. Phung, Trung Le
Improving Multi-task Learning via Seeking Task-based Flat Regions. CoRR (2022)
Khai Nguyen, Nhat Ho
Amortized Projection Optimization for Sliced Wasserstein Generative Models. CoRR (2022)
Dat Do, Nhat Ho, XuanLong Nguyen
Beyond Black Box Densities: Parameter Learning for the Deviated Components. CoRR (2022)
Disha Makhija, Nhat Ho, Joydeep Ghosh
Federated Self-supervised Learning for Heterogeneous Clients. CoRR (2022)
Tan Nguyen, Tam Nguyen, Hai Do, Khai Nguyen, Vishwanath Saragadam, Minh Pham, Duy Khuong Nguyen, Nhat Ho, Stanley J. Osher
Improving Transformer with an Admixture of Attention Heads. NeurIPS (2022)
Tudor A. Manole, Nhat Ho
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models. ICML (2022)
Khai Nguyen, Tongzheng Ren, Huy Nguyen, Litu Rout, Tan Nguyen, Nhat Ho
Hierarchical Sliced Wasserstein Distance. CoRR (2022)
Khai Nguyen, Nhat Ho
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution. NeurIPS (2022)
Khai Nguyen, Nhat Ho
Amortized Projection Optimization for Sliced Wasserstein Generative Models. NeurIPS (2022)
Khang Le, Huy Nguyen, Khai Nguyen, Tung Pham, Nhat Ho
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity. AISTATS (2022)
Khai Nguyen, Nhat Ho
Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution. CoRR (2022)
Khai Nguyen, Dang Nguyen, The-Anh Vu-Le, Tung Pham, Nhat Ho
Improving Mini-batch Optimal Transport via Partial Transportation. ICML (2022)
Khang Le, Dung Q. Le, Huy Nguyen, Dat Do, Tung Pham, Nhat Ho
Entropic Gromov-Wasserstein between Gaussian Distributions. ICML (2022)
Tam Minh Nguyen, Tan Minh Nguyen, Dung D. D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
Improving Transformers with Probabilistic Attention Keys. ICML (2022)
Nhat Ho, Chiao-Yu Yang, Michael I. Jordan
Convergence Rates for Gaussian Mixtures of Experts. J. Mach. Learn. Res. 23 (2022)
Xing Han, Tongzheng Ren, Jing Hu, Joydeep Ghosh, Nhat Ho
Efficient Forecasting of Large Scale Hierarchical Time Series via Multilevel Clustering. CoRR (2022)
Hoang Phan, Ngoc Tran, Trung Le, Toan Tran, Nhat Ho, Dinh Phung
Stochastic Multiple Target Sampling Gradient Descent. NeurIPS (2022)
Nhat Ho, Tongzheng Ren, Sujay Sanghavi, Purnamrita Sarkar, Rachel Ward
An Exponentially Increasing Step-size for Parameter Estimation in Statistical Models. CoRR (2022)
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
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering. CoRR (2022)
Nhat Ho, Tianyi Lin, Michael I. Jordan
On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms. AISTATS (2022)
Dat Do, Nhat Ho, XuanLong Nguyen
Beyond black box densities: Parameter learning for the deviated components. NeurIPS (2022)
Khang Le, Huy Nguyen, Quang Nguyen, Nhat Ho, Tung Pham, Hung Bui
On Robust Optimal Transport: Computational Complexity, Low-rank Approximation, and Barycenter Computation. CoRR (2021)

Nhat Ho.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Nhat Ho