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Hilbert Space Embeddings and Metrics on Probability Measures., , , , and . J. Mach. Learn. Res., (2010)Mixture density estimation via Hilbert space embedding of measures.. ISIT, page 1027-1030. IEEE, (2011)Learning Theory for Distribution Regression., , , and . J. Mach. Learn. Res., (2016)On the Convergence of the Concave-Convex Procedure., and . NIPS, page 1759-1767. Curran Associates, Inc., (2009)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)Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA., and . J. Mach. Learn. Res., (2022)A Fast, Consistent Kernel Two-Sample Test., , , and . NIPS, page 673-681. Curran Associates, Inc., (2009)Optimal kernel choice for large-scale two-sample tests., , , , , , and . NIPS, page 1214-1222. (2012)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)