On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths

24 January 2021

Papers citing "On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths"

7 / 7 papers shown

Title
MLPs at the EOC: Dynamics of Feature Learning Dávid Terjék MLT 36 0 0 18 Feb 2025
Global Convergence Rate of Deep Equilibrium Models with General Activations Lan V. Truong 37 2 0 11 Feb 2023
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 21 4 0 28 Dec 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 22 11 0 15 Nov 2022
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 14 16 0 05 Dec 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 16 73 0 28 Oct 2021
A global convergence theory for deep ReLU implicit networks via over-parameterization Tianxiang Gao Hailiang Liu Jia Liu Hridesh Rajan Hongyang Gao MLT 16 16 0 11 Oct 2021