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A Concentration of Measure and Random Matrix Approach to Large
  Dimensional Robust Statistics
v1v2 (latest)

A Concentration of Measure and Random Matrix Approach to Large Dimensional Robust Statistics

17 June 2020
Cosme Louart
Romain Couillet
ArXiv (abs)PDFHTML

Papers citing "A Concentration of Measure and Random Matrix Approach to Large Dimensional Robust Statistics"

4 / 4 papers shown
Title
Random Matrix Analysis to Balance between Supervised and Unsupervised
  Learning under the Low Density Separation Assumption
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
Vasilii Feofanov
Malik Tiomoko
Aladin Virmaux
56
5
0
20 Oct 2023
Tyler's and Maronna's M-estimators: Non-Asymptotic Concentration Results
Tyler's and Maronna's M-estimators: Non-Asymptotic Concentration Results
Elad Romanov
Gil Kur
B. Nadler
79
3
0
21 Jun 2022
Spectral properties of sample covariance matrices arising from random
  matrices with independent non identically distributed columns
Spectral properties of sample covariance matrices arising from random matrices with independent non identically distributed columns
Cosme Louart
Romain Couillet
37
7
0
06 Sep 2021
A Concentration of Measure Framework to study convex problems and other
  implicit formulation problems in machine learning
A Concentration of Measure Framework to study convex problems and other implicit formulation problems in machine learning
Cosme Louart
19
0
0
19 Oct 2020
1