Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization

15 October 2021

Papers citing "Gradient Descent on Infinitely Wide Neural Networks: Global Convergence and Generalization"

6 / 6 papers shown

Title
Ultra-fast feature learning for the training of two-layer neural networks in the two-timescale regime Raphael Barboni Gabriel Peyré François-Xavier Vialard MLT 39 0 0 25 Apr 2025
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks Luca Arnaboldi Ludovic Stephan Florent Krzakala Bruno Loureiro MLT 38 31 0 12 Feb 2023
Infinite-width limit of deep linear neural networks Lénaïc Chizat Maria Colombo Xavier Fernández-Real Alessio Figalli 31 14 0 29 Nov 2022
$Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias$ Intrinsic dimensionality and generalization properties of the $\mathcal{R}$ -norm inductive bias Navid Ardeshir Daniel J. Hsu Clayton Sanford CML AI4CE 18 6 0 10 Jun 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks R. Veiga Ludovic Stephan Bruno Loureiro Florent Krzakala Lenka Zdeborová MLT 13 31 0 01 Feb 2022
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network Mo Zhou Rong Ge Chi Jin 74 45 0 04 Feb 2021