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`Distribution regression' refers to the situation where a response Y depends on a covariate P where P is a probability distribution.
Nonparametric regression with errors in variables
J. Fan and Y.K. Truong · 1993
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Exploiting generative models in discriminative classifiers
T. Jaakkola and D. Haussler · 1998
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Combinatorial methods in density estimation
L. Devroye and G. Lugosi · 2001
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A Distribution-Free Theory of Nonparametric Regression
L. Györfi, M. Kohler, A. Krzyzak, and H. Walk · 2002
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Introduction to Nonparametric Estimation
A.B. Tsybakov · 2002
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A kernel between sets of vectors
R. Kondor and T. Jebara · 2003
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Probability product kernels
T. Jebara, R. Kondor, A. Howard, K. Bennett, and N. Cesa-bianchi · 2004
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A Kullback-Leibler divergence based kernel for SVM classification in multimedia applications
P. Moreno, P. Ho, and N. Vasconcelos · 2004
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Functional data analysis
J.O. Ramsay and B.W Silverman · 2005
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Measurement error in nonlinear models: a modern perspective , volume 105
R.J. Carroll, D. Ruppert, L.A. Stefanski, and C.M. Crainiceanu · 2006
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Nonparametric Functional Data Analysis: Theory and Practice
F. Ferraty and P. Vieu · 2006
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A Hilbert space embedding for distributions
A. Smola, A. Gretton, L. Song, and B. Schölkopf · 2007
Cited alongside, same era.
Optimal rates for plug-in estimators of density level sets
P. Rigollet and R. Vert · 2009
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Universal kernels on non-standard input spaces
A. Christmann and I. Steinwart · 2010
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k-nn regression adapts to local intrinsic dimension
S. Kpotufe · 2011
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Nonparametric divergence estimation with applications to machine learning on distributions
B. Póczos, L. Xiong, and J. Schneider · 2011
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Learning from distributions via support measure machines
K. Muandet, B. Schölkopf, K. Fukumizu, and F. Dinuzzo · 2012
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Nonparametric kernel estimators for image classification
B. Póczos, L. Xiong, D. Sutherland, and J. Schneider · 2012
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