Benign overfitting and adaptive nonparametric regression

06/27/2022
by   Julien Chhor, et al.
0

In the nonparametric regression setting, we construct an estimator which is a continuous function interpolating the data points with high probability, while attaining minimax optimal rates under mean squared risk on the scale of Hölder classes adaptively to the unknown smoothness.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/03/2018

Estimating the error distribution function in nonparametric regression

We construct an efficient estimator for the error distribution function ...
research
04/06/2020

Nonparametric local linear estimation of the relative error regression function for censorship model

In this paper, we built a new nonparametric regression estimator with th...
research
07/03/2023

Minimax rates of convergence for nonparametric location-scale models

This paper studies minimax rates of convergence for nonparametric locati...
research
04/06/2022

Adaptive warped kernel estimation for nonparametric regression with circular responses

In this paper, we deal with nonparametric regression for circular data, ...
research
04/20/2022

Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?

We study the theory of neural network (NN) from the lens of classical no...
research
12/15/2020

Minimax Risk and Uniform Convergence Rates for Nonparametric Dyadic Regression

Let i=1,…,N index a simple random sample of units drawn from some large ...
research
05/19/2023

Nonparametric classification with missing data

We introduce a new nonparametric framework for classification problems i...

Please sign up or login with your details

Forgot password? Click here to reset