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Learning Lipschitz Functions by GD-trained Shallow Overparameterized
  ReLU Neural Networks

Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks

28 December 2022
Ilja Kuzborskij
Csaba Szepesvári
ArXivPDFHTML

Papers citing "Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks"

5 / 5 papers shown
Title
Near-Interpolators: Rapid Norm Growth and the Trade-Off between
  Interpolation and Generalization
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization
Yutong Wang
Rishi Sonthalia
Wei Hu
25
2
0
12 Mar 2024
Neural Network-Based Score Estimation in Diffusion Models: Optimization
  and Generalization
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
Yinbin Han
Meisam Razaviyayn
Renyuan Xu
DiffM
25
12
0
28 Jan 2024
Fine-grained analysis of non-parametric estimation for pairwise learning
Fine-grained analysis of non-parametric estimation for pairwise learning
Junyu Zhou
Shuo Huang
Han Feng
Puyu Wang
Ding-Xuan Zhou
12
1
0
31 May 2023
Learning Single-Index Models with Shallow Neural Networks
Learning Single-Index Models with Shallow Neural Networks
A. Bietti
Joan Bruna
Clayton Sanford
M. Song
147
65
0
27 Oct 2022
On the Proof of Global Convergence of Gradient Descent for Deep ReLU
  Networks with Linear Widths
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh N. Nguyen
23
49
0
24 Jan 2021
1