Regularization Matters: A Nonparametric Perspective on Overparametrized
Neural Network

Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network

6 July 2020

Tianyang Hu

Papers citing "Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network"

8 / 8 papers shown

Title
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory Guhan Chen Yicheng Li Qian Lin AAML 38 1 0 08 Oct 2024
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains Yicheng Li Zixiong Yu Y. Cotronis Qian Lin 55 13 0 04 May 2023
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 21 4 0 28 Dec 2022
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 324 48 0 29 Sep 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu Jose H. Blanchet Lexing Ying 35 7 0 15 May 2022
Understanding Square Loss in Training Overparametrized Neural Network Classifiers Tianyang Hu Jun Wang Wenjia Wang Zhenguo Li UQCV AAML 35 19 0 07 Dec 2021
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 17 18 0 11 Nov 2021
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 32 214 0 03 Dec 2019