受强制性开放获取政策约束的文章 - Bharath Sriperumbudur了解详情
可在其他位置公开访问的文章：18 篇
Learning theory for distribution regression
Z Szabó, BK Sriperumbudur, B Póczos, A Gretton
Journal of Machine Learning Research 17 (152), 1-40, 2016
强制性开放获取政策： US National Science Foundation, US Department of Energy
Characteristic and universal tensor product kernels
Z Szabó, BK Sriperumbudur
Journal of Machine Learning Research 18 (233), 1-29, 2018
强制性开放获取政策： US National Science Foundation
Kernel mean shrinkage estimators
K Mu, B Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf
Journal of Machine Learning Research 17 (48), 1-41, 2016
强制性开放获取政策： 国家自然科学基金委员会
Convergence analysis of deterministic kernel-based quadrature rules in misspecified settings
M Kanagawa, BK Sriperumbudur, K Fukumizu
Foundations of Computational Mathematics 20, 155-194, 2020
强制性开放获取政策： US National Science Foundation, European Commission
Approximate kernel pca: Computational versus statistical trade-off
BK Sriperumbudur, N Sterge
The Annals of Statistics 50 (5), 2713-2736, 2022
强制性开放获取政策： US National Science Foundation
Optimal prediction for additive function-on-function regression
M Reimherr, B Sriperumbudur, B Taoufik
Electronic Journal of Statistics 12 (2), 4571-4601, 2018
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
On kernel derivative approximation with random Fourier features
Z Szabó, B Sriperumbudur
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
强制性开放获取政策： US National Science Foundation
Cycle consistent probability divergences across different spaces
Z Zhang, Y Mroueh, Z Goldfeld, B Sriperumbudur
International Conference on Artificial Intelligence and Statistics, 7257-7285, 2022
强制性开放获取政策： US National Science Foundation
Local minimax rates for closeness testing of discrete distributions
J Lam-Weil, A Carpentier, BK Sriperumbudur
Bernoulli 28 (2), 1179-1197, 2022
强制性开放获取政策： German Research Foundation
Robust persistence diagrams using reproducing kernels
S Vishwanath, K Fukumizu, S Kuriki, BK Sriperumbudur
Advances in Neural Information Processing Systems 33, 21900-21911, 2020
强制性开放获取政策： US National Science Foundation
Gaussian sketching yields a JL lemma in RKHS
S Kpotufe, B Sriperumbudur
International Conference on Artificial Intelligence and Statistics, 3928-3937, 2020
强制性开放获取政策： US National Science Foundation
Optimal function-on-scalar regression over complex domains
M Reimherr, B Sriperumbudur, HB Kang
Electronic Journal of Statistics 17 (1), 156-197, 2023
强制性开放获取政策： US National Science Foundation
On distance and kernel measures of conditional dependence
T Sheng, BK Sriperumbudur
Journal of Machine Learning Research 24 (7), 1-16, 2023
强制性开放获取政策： US National Science Foundation
Spectral regularized kernel goodness-of-fit tests
O Hagrass, BK Sriperumbudur, B Li
Journal of Machine Learning Research 25 (309), 1-52, 2024
强制性开放获取政策： US National Science Foundation
Minimax-optimal distribution regression
Z Szabó, B Sriperumbudur, B Póczos, A Gretton
International Society for NonParametric Statistics (ISNPS) Conference, 2016
强制性开放获取政策： US National Science Foundation
Adaptive clustering using kernel density estimators
I Steinwart, BK Sriperumbudur, P Thomann
Journal of Machine Learning Research 24 (275), 1-56, 2023
强制性开放获取政策： US National Science Foundation, German Research Foundation
Duality and Sample Complexity for the Gromov-Wasserstein Distance
Z Zhang, Z Goldfeld, Y Mroueh, B Sriperumbudur
NeurIPS 2023 Workshop Optimal Transport and Machine Learning, 2023
强制性开放获取政策： US National Science Foundation
Distribution Regression with Minimax-Optimal Guarantee
Z Szabó, B Sriperumbudur, B Poczos, A Gretton
MASCOT-NUM 2016, 2016
强制性开放获取政策： US National Science Foundation
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