Multilevel clustering via Wasserstein means N Ho, XL Nguyen, M Yurochkin, HH Bui, V Huynh, D Phung Proceedings of the ICML, 2017, 2017 | 151 | 2017 |
On efficient optimal transport: An analysis of greedy and accelerated mirror descent algorithms T Lin*, N Ho*, MI Jordan Proceedings of the ICML, 2019, 2019 | 140 | 2019 |
Distributional sliced-Wasserstein and applications to generative modeling K Nguyen, N Ho, T Pham, H Bui International Conference on Learning Representations (ICLR), 2021, 2021 | 96 | 2021 |
Convergence rates of parameter estimation for some weakly identifiable finite mixtures N Ho, XL Nguyen The Annals of Statistics 44 (6), 2726-2755, 2016 | 92 | 2016 |
On the efficiency of entropic regularized algorithms for optimal transport T Lin, N Ho, MI Jordan Journal of Machine Learning Research (JMLR) 23 (137), 1-42, 2022 | 78* | 2022 |
On unbalanced optimal transport: an analysis of Sinkhorn algorithm K Pham, K Le, N Ho, T Pham, H Bui Proceedings of the ICML, 2020, 2020 | 75 | 2020 |
On the complexity of approximating multimarginal optimal transport T Lin*, N Ho*, M Cuturi, MI Jordan Journal of Machine Learning Research (JMLR) 23 (65), 1-43, 2022 | 74 | 2022 |
On strong identifiability and convergence rates of parameter estimation in finite mixtures N Ho, XL Nguyen Electronic Journal of Statistics 10 (1), 271-307, 2016 | 68 | 2016 |
Point-set distances for learning representations of 3D point clouds T Nguyen, QH Pham, T Le, T Pham, N Ho, BS Hua International Conference on Computer Vision (ICCV), 2021, 2021 | 65 | 2021 |
Fixed-support Wasserstein barycenters: computational hardness and fast algorithm T Lin, N Ho, X Chen, M Cuturi, MI Jordan Advances in NeurIPS, 2020, 2020 | 65* | 2020 |
Projection robust Wasserstein distance and Riemannian optimization T Lin*, C Fan*, N Ho, M Cuturi, MI Jordan Advances in NeurIPS, 2020, 2020 | 65 | 2020 |
Singularity, misspecification, and the convergence rate of EM R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, MI Jordan, B Yu The Annals of Statistics 48(6), 3161-3182, 2020 | 64 | 2020 |
LAMDA: Label matching deep domain adaptation T Le, T Nguyen, N Ho, H Bui, D Phung Proceedings of the ICML, 2021, 2021 | 62* | 2021 |
On posterior contraction of parameters and interpretability in Bayesian mixture modeling A Guha, N Ho, XL Nguyen Bernoulli 27 (4), 2159-2188, 2021 | 58 | 2021 |
Convergence rates for Gaussian mixtures of experts N Ho, CY Yang, MI Jordan Journal of Machine Learning Research, 2022 | 42 | 2022 |
On the minimax optimality of the EM algorithm for learning two-component mixed linear regression JY Kwon, N Ho, C Caramanis International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021 | 41 | 2021 |
Singularity structures and impacts on parameter estimation in finite mixtures of distributions N Ho, XL Nguyen SIAM Journal on Mathematics of Data Science (SIMODS), 1(4), 730–758, 2019 | 38 | 2019 |
Revisiting over-smoothing and over-squashing using Ollivier's Ricci curvature K Nguyen, H Nong, V Nguyen, N Ho, S Osher, T Nguyen Proceedings of the ICML, 2023, 2023 | 37 | 2023 |
Fast algorithms for computational optimal transport and Wasserstein barycenter W Guo, N Ho, MI Jordan International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 37* | 2020 |
Architecture agnostic federated learning for neural networks D Makhija, X Han, N Ho, J Ghosh Proceedings of the ICML, 2022, 2022 | 36 | 2022 |