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Learning curves for the multi-class teacher-student perceptron

Learning curves for the multi-class teacher-student perceptron

22 March 2022
Elisabetta Cornacchia
Francesca Mignacco
R. Veiga
Cédric Gerbelot
Bruno Loureiro
Lenka Zdeborová
ArXivPDFHTML

Papers citing "Learning curves for the multi-class teacher-student perceptron"

14 / 14 papers shown
Title
Provable Weak-to-Strong Generalization via Benign Overfitting
Provable Weak-to-Strong Generalization via Benign Overfitting
David X. Wu
A. Sahai
73
6
0
06 Oct 2024
Nonlinear classification of neural manifolds with contextual information
Nonlinear classification of neural manifolds with contextual information
Francesca Mignacco
Chi-Ning Chou
SueYeon Chung
21
2
0
10 May 2024
A Convergence Analysis of Approximate Message Passing with Non-Separable
  Functions and Applications to Multi-Class Classification
A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification
Burak Çakmak
Yue M. Lu
Manfred Opper
26
4
0
13 Feb 2024
A phase transition between positional and semantic learning in a
  solvable model of dot-product attention
A phase transition between positional and semantic learning in a solvable model of dot-product attention
Hugo Cui
Freya Behrens
Florent Krzakala
Lenka Zdeborová
MLT
33
11
0
06 Feb 2024
The Copycat Perceptron: Smashing Barriers Through Collective Learning
The Copycat Perceptron: Smashing Barriers Through Collective Learning
Giovanni Catania
A. Decelle
Beatriz Seoane
FedML
15
2
0
07 Aug 2023
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models
Precise Asymptotic Generalization for Multiclass Classification with Overparameterized Linear Models
David X. Wu
A. Sahai
26
2
0
23 Jun 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High
  Dimensions
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
28
3
0
17 Jun 2023
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates
  in High-Dimensions
Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
Kai Tan
Pierre C. Bellec
16
5
0
28 May 2023
Phase transitions in the mini-batch size for sparse and dense two-layer
  neural networks
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
Neural-prior stochastic block model
Neural-prior stochastic block model
O. Duranthon
L. Zdeborová
41
3
0
17 Mar 2023
Wigner kernels: body-ordered equivariant machine learning without a
  basis
Wigner kernels: body-ordered equivariant machine learning without a basis
Filippo Bigi
Sergey Pozdnyakov
Michele Ceriotti
32
15
0
07 Mar 2023
Are Gaussian data all you need? Extents and limits of universality in
  high-dimensional generalized linear estimation
Are Gaussian data all you need? Extents and limits of universality in high-dimensional generalized linear estimation
Luca Pesce
Florent Krzakala
Bruno Loureiro
Ludovic Stephan
21
26
0
17 Feb 2023
On double-descent in uncertainty quantification in overparametrized
  models
On double-descent in uncertainty quantification in overparametrized models
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
UQCV
46
12
0
23 Oct 2022
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural
  Networks
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon
Abdulkadir Canatar
C. Pehlevan
144
201
0
07 Feb 2020
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