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Classification of Heavy-tailed Features in High Dimensions: a
  Superstatistical Approach
v1v2v3 (latest)

Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach

6 April 2023
Urte Adomaityte
G. Sicuro
P. Vivo
ArXiv (abs)PDFHTML

Papers citing "Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach"

14 / 14 papers shown
Title
Gaussian Universality of Perceptrons with Random Labels
Gaussian Universality of Perceptrons with Random Labels
Federica Gerace
Florent Krzakala
Bruno Loureiro
Ludovic Stephan
Lenka Zdeborová
88
24
0
26 May 2022
Universality of empirical risk minimization
Universality of empirical risk minimization
Andrea Montanari
Basil Saeed
OOD
63
75
0
17 Feb 2022
Graph-based Approximate Message Passing Iterations
Graph-based Approximate Message Passing Iterations
Cédric Gerbelot
Raphael Berthier
80
48
0
24 Sep 2021
Prevalence of Neural Collapse during the terminal phase of deep learning
  training
Prevalence of Neural Collapse during the terminal phase of deep learning training
Vardan Papyan
Xuemei Han
D. Donoho
202
578
0
18 Aug 2020
Asymptotic Errors for Teacher-Student Convex Generalized Linear Models
  (or : How to Prove Kabashima's Replica Formula)
Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima's Replica Formula)
Cédric Gerbelot
A. Abbara
Florent Krzakala
41
48
0
11 Jun 2020
The role of regularization in classification of high-dimensional noisy
  Gaussian mixture
The role of regularization in classification of high-dimensional noisy Gaussian mixture
Francesca Mignacco
Florent Krzakala
Yue M. Lu
Lenka Zdeborová
40
89
0
26 Feb 2020
Generalisation error in learning with random features and the hidden
  manifold model
Generalisation error in learning with random features and the hidden manifold model
Federica Gerace
Bruno Loureiro
Florent Krzakala
M. Mézard
Lenka Zdeborová
67
172
0
21 Feb 2020
A Model of Double Descent for High-dimensional Binary Linear
  Classification
A Model of Double Descent for High-dimensional Binary Linear Classification
Zeyu Deng
A. Kammoun
Christos Thrampoulidis
85
146
0
13 Nov 2019
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting
Marc Lelarge
Léo Miolane
49
28
0
08 Jul 2019
Limitations of Lazy Training of Two-layers Neural Networks
Limitations of Lazy Training of Two-layers Neural Networks
Behrooz Ghorbani
Song Mei
Theodor Misiakiewicz
Andrea Montanari
MLT
55
143
0
21 Jun 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
194
743
0
19 Mar 2019
Reconciling modern machine learning practice and the bias-variance
  trade-off
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
240
1,650
0
28 Dec 2018
Conditional predictive inference for stable algorithms
Conditional predictive inference for stable algorithms
Lukas Steinberger
Hannes Leeb
161
12
0
05 Sep 2018
State Evolution for General Approximate Message Passing Algorithms, with
  Applications to Spatial Coupling
State Evolution for General Approximate Message Passing Algorithms, with Applications to Spatial Coupling
Adel Javanmard
Andrea Montanari
75
263
0
21 Nov 2012
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