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2202.00293
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Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
1 February 2022
R. Veiga
Ludovic Stephan
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
MLT
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Papers citing
"Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks"
30 / 30 papers shown
Title
Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning
Andrew Bond
Zafer Dogan
25
0
0
01 Nov 2024
A Random Matrix Theory Perspective on the Spectrum of Learned Features and Asymptotic Generalization Capabilities
Yatin Dandi
Luca Pesce
Hugo Cui
Florent Krzakala
Yue M. Lu
Bruno Loureiro
MLT
39
1
0
24 Oct 2024
A theoretical perspective on mode collapse in variational inference
Roman Soletskyi
Marylou Gabrié
Bruno Loureiro
DRL
37
2
0
17 Oct 2024
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory
Francesco Mori
Stefano Sarao Mannelli
Francesca Mignacco
36
3
0
26 Sep 2024
Training Dynamics of Nonlinear Contrastive Learning Model in the High Dimensional Limit
Lineghuan Meng
Chuang Wang
28
1
0
11 Jun 2024
Online Learning and Information Exponents: On The Importance of Batch size, and Time/Complexity Tradeoffs
Luca Arnaboldi
Yatin Dandi
Florent Krzakala
Bruno Loureiro
Luca Pesce
Ludovic Stephan
47
1
0
04 Jun 2024
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features
Rodrigo Veiga
Anastasia Remizova
Nicolas Macris
40
0
0
12 Feb 2024
Should Under-parameterized Student Networks Copy or Average Teacher Weights?
Berfin Simsek
Amire Bendjeddou
W. Gerstner
Johanni Brea
32
7
0
03 Nov 2023
Learning Dynamics in Linear VAE: Posterior Collapse Threshold, Superfluous Latent Space Pitfalls, and Speedup with KL Annealing
Yuma Ichikawa
Koji Hukushima
26
5
0
24 Oct 2023
On the different regimes of Stochastic Gradient Descent
Antonio Sclocchi
M. Wyart
31
18
0
19 Sep 2023
Stochastic Gradient Descent outperforms Gradient Descent in recovering a high-dimensional signal in a glassy energy landscape
Persia Jana Kamali
Pierfrancesco Urbani
25
6
0
09 Sep 2023
Minibatch training of neural network ensembles via trajectory sampling
Jamie F. Mair
Luke Causer
J. P. Garrahan
19
0
0
23 Jun 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
36
3
0
17 Jun 2023
Escaping mediocrity: how two-layer networks learn hard generalized linear models with SGD
Luca Arnaboldi
Florent Krzakala
Bruno Loureiro
Ludovic Stephan
MLT
37
3
0
29 May 2023
Phase transitions in the mini-batch size for sparse and dense two-layer neural networks
Raffaele Marino
F. Ricci-Tersenghi
30
14
0
10 May 2023
Leveraging the two timescale regime to demonstrate convergence of neural networks
Pierre Marion
Raphael Berthier
36
5
0
19 Apr 2023
Mapping of attention mechanisms to a generalized Potts model
Riccardo Rende
Federica Gerace
Alessandro Laio
Sebastian Goldt
17
22
0
14 Apr 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
38
29
0
06 Apr 2023
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Krishnakumar Balasubramanian
Promit Ghosal
Ye He
38
5
0
03 Apr 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
38
31
0
12 Feb 2023
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization
R. Srinivasan
Francesca Mignacco
M. Sorbaro
Maria Refinetti
A. Cooper
Gabriel Kreiman
Giorgia Dellaferrera
32
15
0
10 Feb 2023
Learning Single-Index Models with Shallow Neural Networks
A. Bietti
Joan Bruna
Clayton Sanford
M. Song
170
68
0
27 Oct 2022
Rigorous dynamical mean field theory for stochastic gradient descent methods
Cédric Gerbelot
Emanuele Troiani
Francesca Mignacco
Florent Krzakala
Lenka Zdeborova
38
26
0
12 Oct 2022
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
Alireza Mousavi-Hosseini
Sejun Park
M. Girotti
Ioannis Mitliagkas
Murat A. Erdogdu
MLT
324
48
0
29 Sep 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy
Michael Celentano
46
20
0
19 Aug 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Gerard Ben Arous
Reza Gheissari
Aukosh Jagannath
62
58
0
08 Jun 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Jimmy Ba
Murat A. Erdogdu
Taiji Suzuki
Zhichao Wang
Denny Wu
Greg Yang
MLT
42
121
0
03 May 2022
Data-driven emergence of convolutional structure in neural networks
Alessandro Ingrosso
Sebastian Goldt
61
38
0
01 Feb 2022
The dynamics of representation learning in shallow, non-linear autoencoders
Maria Refinetti
Sebastian Goldt
AI4CE
20
17
0
06 Jan 2022
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach
Grant M. Rotskoff
Eric Vanden-Eijnden
68
118
0
02 May 2018
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