On Feature Learning in Neural Networks with Global Convergence
Guarantees

On Feature Learning in Neural Networks with Global Convergence Guarantees

22 April 2022

Eric Vanden-Eijnden

Joan Bruna

Papers citing "On Feature Learning in Neural Networks with Global Convergence Guarantees"

8 / 8 papers shown

Title
Convergence of Shallow ReLU Networks on Weakly Interacting Data Léo Dana Francis R. Bach Loucas Pillaud-Vivien MLT 52 1 0 24 Feb 2025
Curse of Dimensionality in Neural Network Optimization Sanghoon Na Haizhao Yang 56 0 0 07 Feb 2025
Generalization of Scaled Deep ResNets in the Mean-Field Regime Yihang Chen Fanghui Liu Yiping Lu Grigorios G. Chrysos V. Cevher 41 2 0 14 Mar 2024
Rethinking Gauss-Newton for learning over-parameterized models Michael Arbel Romain Menegaux Pierre Wolinski AI4CE 16 5 0 06 Feb 2023
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning François Caron Fadhel Ayed Paul Jung Hoileong Lee Juho Lee Hongseok Yang 62 2 0 02 Feb 2023
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs Etienne Boursier Loucas Pillaud-Vivien Nicolas Flammarion ODL 19 58 0 02 Jun 2022
Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates Jingwei Zhang Xunpeng Huang Jincheng Yu MLT 18 1 0 19 May 2022
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network Mo Zhou Rong Ge Chi Jin 74 44 0 04 Feb 2021