On the rate of convergence of fully connected deep neural network regression estimates
From MaRDI portal
Publication:2054491
DOI10.1214/20-AOS2034zbMath1486.62112arXiv1908.11133MaRDI QIDQ2054491
Publication date: 3 December 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1908.11133
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Artificial neural networks and deep learning (68T07)
Related Items
Convergence rates of deep ReLU networks for multiclass classification, Estimation of a regression function on a manifold by fully connected deep neural networks, A Deep Generative Approach to Conditional Sampling, Asymptotic properties of neural network sieve estimators, Convergence rates for shallow neural networks learned by gradient descent, Deep nonparametric regression on approximate manifolds: nonasymptotic error bounds with polynomial prefactors, Optimal convergence rates of deep neural networks in a classification setting, Adaptive variational Bayes: optimality, computation and applications, Asset pricing with neural networks: significance tests, Analysis of the rate of convergence of two regression estimates defined by neural features which are easy to implement, Intrinsic and extrinsic deep learning on manifolds, On the rate of convergence of a deep recurrent neural network estimate in a regression problem with dependent data, On the rate of convergence of image classifiers based on convolutional neural networks, Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling
Cites Work
- Unnamed Item
- Unnamed Item
- Additive regression and other nonparametric models
- Distribution-free consistency results in nonparametric discrimination and regression function estimation
- Approximation and estimation bounds for artificial neural networks
- The use of polynomial splines and their tensor products in multivariate function estimation. (With discussion)
- Optimal global rates of convergence for nonparametric regression
- A distribution-free theory of nonparametric regression
- Nonparametric regression using deep neural networks with ReLU activation function
- On deep learning as a remedy for the curse of dimensionality in nonparametric regression
- Optimal smoothing in single-index models
- Rate-optimal estimation for a general class of nonparametric regression models with unknown link functions
- Deep vs. shallow networks: An approximation theory perspective
- Adaptive regression estimation with multilayer feedforward neural networks
- Investigating Smooth Multiple Regression by the Method of Average Derivatives
- Variable selection for the single-index model
- Universal approximation bounds for superpositions of a sigmoidal function
- Penalized Spline Estimation for Partially Linear Single-Index Models
- Deep Neural Network Approximation Theory
- Deep Network Approximation for Smooth Functions
- Nonparametric Regression Based on Hierarchical Interaction Models