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Stochasticity helps to navigate rough landscapes: comparing
  gradient-descent-based algorithms in the phase retrieval problem
v1v2 (latest)

Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem

8 March 2021
Francesca Mignacco
Pierfrancesco Urbani
Lenka Zdeborová
ArXiv (abs)PDFHTML

Papers citing "Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem"

11 / 11 papers shown
Title
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
Vittorio Erba
Emanuele Troiani
Luca Biggio
Antoine Maillard
Lenka Zdeborová
202
2
0
24 Oct 2024
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis
  dynamics in discrete optimization and inference problems
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems
Maria Chiara Angelini
A. Cavaliere
Raffaele Marino
F. Ricci-Tersenghi
122
5
0
11 Sep 2023
Gradient flow in the gaussian covariate model: exact solution of
  learning curves and multiple descent structures
Gradient flow in the gaussian covariate model: exact solution of learning curves and multiple descent structures
Antione Bodin
N. Macris
74
4
0
13 Dec 2022
Disordered Systems Insights on Computational Hardness
Disordered Systems Insights on Computational Hardness
D. Gamarnik
Cristopher Moore
Lenka Zdeborová
AI4CE
84
36
0
15 Oct 2022
Rigorous dynamical mean field theory for stochastic gradient descent
  methods
Rigorous dynamical mean field theory for stochastic gradient descent methods
Cédric Gerbelot
Emanuele Troiani
Francesca Mignacco
Florent Krzakala
Lenka Zdeborova
114
29
0
12 Oct 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide
  Neural Networks
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
87
85
0
19 May 2022
The effective noise of Stochastic Gradient Descent
The effective noise of Stochastic Gradient Descent
Francesca Mignacco
Pierfrancesco Urbani
69
39
0
20 Dec 2021
Model, sample, and epoch-wise descents: exact solution of gradient flow
  in the random feature model
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model
A. Bodin
N. Macris
123
13
0
22 Oct 2021
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations,
  and Anomalous Diffusion
The Limiting Dynamics of SGD: Modified Loss, Phase Space Oscillations, and Anomalous Diffusion
D. Kunin
Javier Sagastuy-Breña
Lauren Gillespie
Eshed Margalit
Hidenori Tanaka
Surya Ganguli
Daniel L. K. Yamins
93
20
0
19 Jul 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons
On the Cryptographic Hardness of Learning Single Periodic Neurons
M. Song
Ilias Zadik
Joan Bruna
AAML
68
28
0
20 Jun 2021
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic
  High-Dimensional Non-Convex Problems
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems
Stefano Sarao Mannelli
Pierfrancesco Urbani
61
10
0
23 Feb 2021
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