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Kernel mean embeddings are a popular tool that consists in representing probability measures by their infinite-dimensional mean embeddings in a reproducing kernel Hilbert space.
A useful convergence theorem for probability distributions
Henry Scheffé · 1947
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On estimation of a probability density function and mode
Emanuel Parzen · 1962
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Density Estimation for Statistics and Data Analysis
B. W. Silverman · 1986
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A linear-time median-finding algorithm for projecting a vector on the simplex of ℝ n \mathbb{R}^{n}
Nelson Maculan and Geraldo Galdino de Paula Jr · 1989
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Sobolev Spaces
Robert A. Adams and John J. F. Fournier · 2003
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The pre-image problem in kernel methods
J.T.-Y. Kwok and I.W.-H. Tsang · 2004
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A dual approach to semidefinite least-squares problems
Jérôme Malick · 2004
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Least-squares covariance matrix adjustment
Stephen Boyd and Lin Xiao · 2005
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Universal kernels
Charles A Micchelli, Yuesheng Xu, and Haizhang Zhang · 2006
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Support Vector Machines
Ingo Steinwart and Andreas Christmann · 2008
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A fast iterative shrinkage-thresholding algorithm for linear inverse problems
Amir Beck and Marc Teboulle · 2009
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Bharath K. Sriperumbudur, Kenji Fukumizu, and Gert R. G. Lanckriet · 2011
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Equivalence of distance-based and rkhs-based statistics in hypothesis testing
Dino Sejdinovic, Bharath Sriperumbudur, Arthur Gretton, and Kenji Fukumizu · 2013
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Kernel mean embedding of distributions: A review and beyond
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Bernhard Schölkopf, et al · 2017
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Falkon: an optimal large scale kernel method
Alessandro Rudi, Luigi Carratino, and Lorenzo Rosasco · 2017
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Demystifying mmd gans
Mikołaj Bińkowski, Dougal J Sutherland, Michael Arbel, and Arthur Gretton · 2018
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Distributionally robust optimization: A review
Hamed Rahimian and Sanjay Mehrotra · 2019
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Distributionally robust optimization and generalization in kernel methods
Matthew Staib and Stefanie Jegelka · 2019
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Non-parametric models for non-negative functions
Ulysse Marteau-Ferey, Francis Bach, and Alessandro Rudi · 2020
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Generative moment matching networks
Yujia Li, Kevin Swersky, and Rich Zemel · 2015
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An Introduction to the Theory of Reproducing Kernel Hilbert Spaces , volume 152
Vern I. Paulsen and Mrinal Raghupathi · 2016
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Metrizing weak convergence with maximum mean discrepancies
Carl-Johann Simon-Gabriel, Alessandro Barp, and Lester Mackey · 2020
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Kernel distributionally robust optimization: Generalized duality theorem and stochastic approximation
Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, and Bernhard Schölkopf · 2021
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