Near-optimal coresets of kernel density estimates JM Phillips, WM Tai Discrete & Computational Geometry 63, 867-887, 2020 | 75 | 2020 |
Improved coresets for kernel density estimates JM Phillips, WM Tai Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 43 | 2018 |
Tracking the frequency moments at all times Z Huang, WM Tai, K Yi arXiv preprint arXiv:1412.1763, 2014 | 15* | 2014 |
Optimal estimation of Gaussian DAG models M Gao, WM Tai, B Aragam International Conference on Artificial Intelligence and Statistics, 8738-8757, 2022 | 13 | 2022 |
Finding an approximate mode of a kernel density estimate JCH Lee, J Li, C Musco, JM Phillips, WM Tai 29th Annual European Symposium on Algorithms (ESA 2021), 2021 | 11* | 2021 |
Optimal Coreset for Gaussian Kernel Density Estimation WM Tai arXiv preprint arXiv:2007.08031, 2020 | 9* | 2020 |
The gaussiansketch for almost relative error kernel distance P Jeff, T Wai Ming International Conference on Randomization and Computation (RANDOM), 2020 | 6* | 2020 |
Agnostic active learning of single index models with linear sample complexity A Gajjar, WM Tai, X Xingyu, C Hegde, C Musco, Y Li The Thirty Seventh Annual Conference on Learning Theory, 1715-1754, 2024 | 2 | 2024 |
Approximate Guarantees for Dictionary Learning A Bhaskara, WM Tai Conference on Learning Theory, 299-317, 2019 | 2 | 2019 |
Tight bounds on the hardness of learning simple nonparametric mixtures WM Tai, B Aragam The Thirty Sixth Annual Conference on Learning Theory, 2849-2849, 2023 | 1 | 2023 |
Learning in practice: Reasoning about quantization A Cherkaev, W Tai, J Phillips, V Srikumar arXiv preprint arXiv:1905.11478, 2019 | 1 | 2019 |
Optimal estimation of Gaussian (poly) trees Y Wang, M Gao, WM Tai, B Aragam, A Bhattacharyya International Conference on Artificial Intelligence and Statistics, 3619-3627, 2024 | | 2024 |
Inconsistency of cross-validation for structure learning in Gaussian graphical models Z Lyu, WM Tai, M Kolar, B Aragam International Conference on Artificial Intelligence and Statistics, 3691-3699, 2024 | | 2024 |
On Mergable Coresets for Polytope Distance B Shi, A Bhaskara, WM Tai, JM Phillips arXiv preprint arXiv:2311.05651, 2023 | | 2023 |
Learning mixtures of Gaussians with censored data WM Tai, B Aragam International Conference on Machine Learning, 33396-33415, 2023 | | 2023 |
Optimal neighbourhood selection in structural equation models M Gao, WM Tai, B Aragam arXiv preprint arXiv:2306.02244, 2023 | | 2023 |
Geometry of Kernel Density Estimation WM Tai The University of Utah, 2021 | | 2021 |