Approximation and Estimation for High-Dimensional Deep Learning Networks

10 September 2018

Papers citing "Approximation and Estimation for High-Dimensional Deep Learning Networks"

12 / 12 papers shown

Title
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss T. Getu Georges Kaddoum M. Bennis 40 1 0 13 Sep 2023
Nonlinear controllability and function representation by neural stochastic differential equations Tanya Veeravalli Maxim Raginsky DiffM 11 2 0 01 Dec 2022
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality Lukas Gonon 15 35 0 14 Jun 2021
Neural Network Approximation: Three Hidden Layers Are Enough Zuowei Shen Haizhao Yang Shijun Zhang 24 115 0 25 Oct 2020
Complexity Measures for Neural Networks with General Activation Functions Using Path-based Norms Zhong Li Chao Ma Lei Wu 18 24 0 14 Sep 2020
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning Lin Liu Rajarshi Mukherjee J. M. Robins CML 33 16 0 07 Aug 2020
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 28 10 0 28 Jun 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
A Priori Estimates of the Population Risk for Residual Networks E. Weinan Chao Ma Qingcan Wang UQCV 29 61 0 06 Mar 2019
Generalization Error in Deep Learning Daniel Jakubovitz Raja Giryes M. Rodrigues AI4CE 21 109 0 03 Aug 2018
$Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls$ Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $\ell^1$ and $\ell^0$ Controls Jason M. Klusowski Andrew R. Barron 130 142 0 26 Jul 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015