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Dynamics of stochastic gradient descent for two-layer neural networks in
  the teacher-student setup
v1v2 (latest)

Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup

Neural Information Processing Systems (NeurIPS), 2019
18 June 2019
Sebastian Goldt
Madhu S. Advani
Andrew M. Saxe
Florent Krzakala
Lenka Zdeborová
    MLT
ArXiv (abs)PDFHTML

Papers citing "Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup"

8 / 108 papers shown
Title
Neural Networks and Polynomial Regression. Demystifying the
  Overparametrization Phenomena
Neural Networks and Polynomial Regression. Demystifying the Overparametrization Phenomena
Matt Emschwiller
D. Gamarnik
Eren C. Kizildag
Ilias Zadik
138
9
0
23 Mar 2020
Sharp Rate of Convergence for Deep Neural Network Classifiers under the
  Teacher-Student Setting
Sharp Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting
Tianyang Hu
Zuofeng Shang
Guang Cheng
198
19
0
19 Jan 2020
Data-Dependence of Plateau Phenomenon in Learning with Neural Network
  --- Statistical Mechanical Analysis
Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical AnalysisNeural Information Processing Systems (NeurIPS), 2020
Yuki Yoshida
M. Okada
126
40
0
10 Jan 2020
Analytic expressions for the output evolution of a deep neural network
Analytic expressions for the output evolution of a deep neural network
Anastasia Borovykh
87
0
0
18 Dec 2019
Mean-field inference methods for neural networks
Mean-field inference methods for neural networks
Marylou Gabrié
AI4CE
307
34
0
03 Nov 2019
Hidden Unit Specialization in Layered Neural Networks: ReLU vs.
  Sigmoidal Activation
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation
Elisa Oostwal
Michiel Straat
Michael Biehl
MLT
217
63
0
16 Oct 2019
Student Specialization in Deep ReLU Networks With Finite Width and Input
  Dimension
Student Specialization in Deep ReLU Networks With Finite Width and Input Dimension
Yuandong Tian
MLT
180
8
0
30 Sep 2019
Modelling the influence of data structure on learning in neural
  networks: the hidden manifold model
Modelling the influence of data structure on learning in neural networks: the hidden manifold model
Sebastian Goldt
M. Mézard
Florent Krzakala
Lenka Zdeborová
BDL
278
49
0
25 Sep 2019
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