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Strictly proper kernel scores are well-known tool in probabilistic forecasting, while characteristic kernels have been extensively investigated in the machine learning literature.
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G. B. Folland · 1995
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V. A. Menegatto · 1995
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Measure and Integration Theory
H. Bauer · 2001
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On the influence of the kernel on the consistency of support vector machines
I. Steinwart · 2001
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A necessary and sufficient condition for strictly positive definite functions on spheres
Kernel measures of conditional dependence
K. Fukumizu, A. Gretton, X. Sun, and B. Schölkopf · 2008
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Support Vector Machines
I. Steinwart and A. Christmann · 2008
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Characteristic kernels on groups and semigroups
K. Fukumizu, B. Sriperumbudur, A. Gretton, and B. Schölkopf · 2009
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Release date 2011-08-29
Digital Library of Mathematical Functions (DLMF) · 2011
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Universality, characteristic kernels and RKHS embedding of measures
B. K. Sriperumbudur, K. Fukumizu, and G. R. G. Lanckriet · 2011
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Mercer’s theorem on general domains: on the interaction between measures, kernels, and RKHSs
I. Steinwart and C. Scovel · 2012
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D. Chen, V. A. Menegatto, and X. Sun · 2003
Cited alongside, same era.
Strictly positive definite kernels on subsets of the complex plane
V. A. Menegatto, C. P. Oliveira, and A. P. Peron · 2006
Cited alongside, same era.
Universal kernels
C. A. Micchelli, Y. Xu, and H. Zhang · 2006
Cited alongside, same era.
Function classes that approximate the Bayes risk
I. Steinwart, D. Hush, and C. Scovel · 2006
Cited alongside, same era.
Strictly proper scoring rules, prediction, and estimation
T. Gneiting and A. E. Raftery · 2007
Cited alongside, same era.
A kernel method for the two-sample-problem
A. Gretton, K.M. Borgwardt, M. Rasch, B. Schölkopf, and A.J. Smola · 2007
Cited alongside, same era.
Strictly and non-strictly positive definite functions on spheres
T. Gneiting · 2013
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The Structure of Compact Groups: A Primer for the Student – A Handbook for the Expert
K.H. Hofmann and S.A. Morris · 2013
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Probabilistic forecasting
T. Gneiting and M. Katzfuss · 2014
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Universalities of reproducing kernels revisited
W. Chen, B. Wang, and H. Zhang · 2016
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C.-J. Simon-Gabriel and B. Schölkopf · 2016
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Learning with hierarchical Gaussian kernels
I. Steinwart, P. Thomann, and N. Schmid · 2016
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Kernel mean embedding of distributions: A review and beyond
K. Muandet, K. Fukumizu, B. Sriperumbudur, and B. Schölkopf · 2017
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