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Polynomial-time Sparse Measure Recovery: From Mean Field Theory to
  Algorithm Design

Polynomial-time Sparse Measure Recovery: From Mean Field Theory to Algorithm Design

16 April 2022
Hadi Daneshmand
Francis R. Bach
ArXivPDFHTML

Papers citing "Polynomial-time Sparse Measure Recovery: From Mean Field Theory to Algorithm Design"

2 / 2 papers shown
Title
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
159
235
0
04 Mar 2020
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train
  10,000-Layer Vanilla Convolutional Neural Networks
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
Lechao Xiao
Yasaman Bahri
Jascha Narain Sohl-Dickstein
S. Schoenholz
Jeffrey Pennington
244
349
0
14 Jun 2018
1