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1910.12837
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Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval
28 October 2019
Yan Shuo Tan
Roman Vershynin
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Papers citing
"Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval"
10 / 10 papers shown
Title
Grokking as a First Order Phase Transition in Two Layer Networks
Noa Rubin
Inbar Seroussi
Z. Ringel
37
15
0
05 Oct 2023
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
Alexandru Damian
Eshaan Nichani
Rong Ge
Jason D. Lee
MLT
36
33
0
18 May 2023
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Krishnakumar Balasubramanian
Promit Ghosal
Ye He
30
5
0
03 Apr 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Bhavya Agrawalla
Krishnakumar Balasubramanian
Promit Ghosal
23
2
0
20 Feb 2023
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks
Luca Arnaboldi
Ludovic Stephan
Florent Krzakala
Bruno Loureiro
MLT
30
31
0
12 Feb 2023
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
Satyen Kale
Jason D. Lee
Chris De Sa
Ayush Sekhari
Karthik Sridharan
24
4
0
13 Oct 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
R. Veiga
Ludovic Stephan
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
MLT
10
31
0
01 Feb 2022
On Uniform Boundedness Properties of SGD and its Momentum Variants
Xiaoyu Wang
M. Johansson
23
3
0
25 Jan 2022
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
Robert Mansel Gower
Othmane Sebbouh
Nicolas Loizou
25
74
0
18 Jun 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias
Lu Yu
Krishnakumar Balasubramanian
S. Volgushev
Murat A. Erdogdu
32
50
0
14 Jun 2020
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