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Spectral Evolution and Invariance in Linear-width Neural Networks

Spectral Evolution and Invariance in Linear-width Neural Networks

11 November 2022
Zhichao Wang
A. Engel
Anand D. Sarwate
Ioana Dumitriu
Tony Chiang
ArXivPDFHTML

Papers citing "Spectral Evolution and Invariance in Linear-width Neural Networks"

5 / 5 papers shown
Title
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Behrad Moniri
Donghwan Lee
Hamed Hassani
Edgar Dobriban
MLT
16
19
0
11 Oct 2023
Evaluating natural language processing models with generalization
  metrics that do not need access to any training or testing data
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data
Yaoqing Yang
Ryan Theisen
Liam Hodgkinson
Joseph E. Gonzalez
Kannan Ramchandran
Charles H. Martin
Michael W. Mahoney
72
17
0
06 Feb 2022
Improved Overparametrization Bounds for Global Convergence of Stochastic
  Gradient Descent for Shallow Neural Networks
Improved Overparametrization Bounds for Global Convergence of Stochastic Gradient Descent for Shallow Neural Networks
Bartlomiej Polaczyk
J. Cyranka
ODL
20
3
0
28 Jan 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
The large learning rate phase of deep learning: the catapult mechanism
The large learning rate phase of deep learning: the catapult mechanism
Aitor Lewkowycz
Yasaman Bahri
Ethan Dyer
Jascha Narain Sohl-Dickstein
Guy Gur-Ari
ODL
146
198
0
04 Mar 2020
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