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Implicit Convex Regularizers of CNN Architectures: Convex Optimization
  of Two- and Three-Layer Networks in Polynomial Time

Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time

26 June 2020
Tolga Ergen
Mert Pilanci
ArXivPDFHTML

Papers citing "Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time"

3 / 3 papers shown
Title
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex
  Optimization Formulations for Two-layer Networks
Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks
Mert Pilanci
Tolga Ergen
57
118
0
24 Feb 2020
How do infinite width bounded norm networks look in function space?
How do infinite width bounded norm networks look in function space?
Pedro H. P. Savarese
Itay Evron
Daniel Soudry
Nathan Srebro
39
166
0
13 Feb 2019
Gradient Descent Quantizes ReLU Network Features
Gradient Descent Quantizes ReLU Network Features
Hartmut Maennel
Olivier Bousquet
Sylvain Gelly
MLT
30
80
0
22 Mar 2018
1