Fetching the paper…
Reading the bibliography…
We show that learning methods interpolating the training data can achieve optimal rates for the problems of nonparametric regression and prediction with square loss.
On estimating regression
Elizbar A Nadaraya · 1964
Earlier work this paper cites.
Geoffrey S Watson · 1964
Earlier work this paper cites.
Nearest neighbor pattern classification
Thomas Cover and Peter Hart · 1967
Earlier work this paper cites.
A two-dimensional interpolation function for irregularly-spaced data
Donald Shepard · 1968
Earlier work this paper cites.
Surfaces generated by moving least squares methods
Peter Lancaster and Kes Salkauskas · 1981
Cited alongside, same era.
Nonparametric identification and smoothing of data (Local approximation methods)
V Katkovnik · 1985
Cited alongside, same era.
A probabilistic theory of pattern recognition
Luc Devroye, László Györfi, and Gábor Lugosi · 1996
Cited alongside, same era.
The Hilbert kernel regression estimate
Luc Devroye, Laszlo Györfi, and Adam Krzyżak · 1998
Cited alongside, same era.
Introduction to nonparametric estimation
Alexandre B Tsybakov · 2009
Later among the works it cites.
Rates of convergence for nearest neighbor classification
Kamalika Chaudhuri and Sanjoy Dasgupta · 2014
Later among the works it cites.
Empirical entropy, minimax regret and minimax risk
Alexander Rakhlin, Karthik Sridharan, and Alexandre B Tsybakov · 2017
Later among the works it cites.
Overfitting or perfect fitting? risk bounds for classification and regression rules that interpolate
Mikhail Belkin, Daniel Hsu, and Partha Mitra · 2018
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…