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Two-stage sampled learning theory on distributions.

, , , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)

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Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA., and . J. Mach. Learn. Res., (2022)Consistency and Rates for Clustering with DBSCAN., and . AISTATS, volume 22 of JMLR Proceedings, page 1090-1098. JMLR.org, (2012)On Kernel Derivative Approximation with Random Fourier Features., and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 827-836. PMLR, (2019)Optimal kernel choice for large-scale two-sample tests., , , , , , and . NIPS, page 1214-1222. (2012)A Fast, Consistent Kernel Two-Sample Test., , , and . NIPS, page 673-681. Curran Associates, Inc., (2009)Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3642-3652. PMLR, (2020)Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding., , , and . CoRR, (2014)Minimax Estimation of Quadratic Fourier Functionals., , and . CoRR, (2018)Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint., , and . NIPS, page 1773-1781. (2011)Two-stage sampled learning theory on distributions., , , and . AISTATS, volume 38 of JMLR Workshop and Conference Proceedings, JMLR.org, (2015)