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Stable Recovery of Entangled Weights: Towards Robust Identification of
  Deep Neural Networks from Minimal Samples

Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples

18 January 2021
Christian Fiedler
M. Fornasier
T. Klock
Michael Rauchensteiner
    OOD
ArXivPDFHTML

Papers citing "Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples"

4 / 4 papers shown
Title
Learning ReLU networks to high uniform accuracy is intractable
Learning ReLU networks to high uniform accuracy is intractable
Julius Berner
Philipp Grohs
F. Voigtlaender
32
4
0
26 May 2022
Landscape analysis of an improved power method for tensor decomposition
Landscape analysis of an improved power method for tensor decomposition
Joe Kileel
T. Klock
João M. Pereira
19
10
0
29 Oct 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer
  Neural Network
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
Mo Zhou
Rong Ge
Chi Jin
69
44
0
04 Feb 2021
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
225
2,543
0
25 Jan 2016
1