ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2108.08198
  4. Cited By
Dimension-free Bounds for Sums of Independent Matrices and Simple
  Tensors via the Variational Principle

Dimension-free Bounds for Sums of Independent Matrices and Simple Tensors via the Variational Principle

18 August 2021
Nikita Zhivotovskiy
ArXivPDFHTML

Papers citing "Dimension-free Bounds for Sums of Independent Matrices and Simple Tensors via the Variational Principle"

25 / 25 papers shown
Title
Simple Relative Deviation Bounds for Covariance and Gram Matrices
Simple Relative Deviation Bounds for Covariance and Gram Matrices
Daniel Barzilai
Ohad Shamir
49
1
0
08 Oct 2024
Time-Uniform Confidence Spheres for Means of Random Vectors
Time-Uniform Confidence Spheres for Means of Random Vectors
Ben Chugg
Hongjian Wang
Aaditya Ramdas
126
5
0
14 Nov 2023
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
Mathieu Even
Laurent Massoulié
47
14
0
04 Feb 2021
A law of robustness for two-layers neural networks
A law of robustness for two-layers neural networks
Sébastien Bubeck
Yuanzhi Li
Dheeraj M. Nagaraj
62
57
0
30 Sep 2020
Robust $k$-means Clustering for Distributions with Two Moments
Robust kkk-means Clustering for Distributions with Two Moments
Yegor Klochkov
Alexey Kroshnin
Nikita Zhivotovskiy
43
19
0
06 Feb 2020
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
Halyun Jeong
Xiaowei Li
Y. Plan
Özgür Yilmaz
50
18
0
28 Jan 2020
Exact minimax risk for linear least squares, and the lower tail of
  sample covariance matrices
Exact minimax risk for linear least squares, and the lower tail of sample covariance matrices
Jaouad Mourtada
55
51
0
23 Dec 2019
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for
  Covariance Matrices and Sketching
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching
Miles E. Lopes
N. Benjamin Erichson
Michael W. Mahoney
100
12
0
13 Sep 2019
Mean estimation and regression under heavy-tailed distributions--a
  survey
Mean estimation and regression under heavy-tailed distributions--a survey
Gabor Lugosi
S. Mendelson
93
242
0
10 Jun 2019
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions
Affine Invariant Covariance Estimation for Heavy-Tailed Distributions
Dmitrii Ostrovskii
Alessandro Rudi
47
10
0
08 Feb 2019
Uniform Hanson-Wright type concentration inequalities for unbounded
  entries via the entropy method
Uniform Hanson-Wright type concentration inequalities for unbounded entries via the entropy method
Yegor Klochkov
Nikita Zhivotovskiy
42
30
0
09 Dec 2018
Robust covariance estimation under $L_4-L_2$ norm equivalence
Robust covariance estimation under L4−L2L_4-L_2L4​−L2​ norm equivalence
S. Mendelson
Nikita Zhivotovskiy
82
61
0
27 Sep 2018
Dimension-free PAC-Bayesian bounds for the estimation of the mean of a
  random vector
Dimension-free PAC-Bayesian bounds for the estimation of the mean of a random vector
O. Catoni
Ilaria Giulini
33
30
0
12 Feb 2018
Dimension-free PAC-Bayesian bounds for matrices, vectors, and linear
  least squares regression
Dimension-free PAC-Bayesian bounds for matrices, vectors, and linear least squares regression
O. Catoni
Ilaria Giulini
39
66
0
07 Dec 2017
Asymptotically Efficient Estimation of Smooth Functionals of Covariance
  Operators
Asymptotically Efficient Estimation of Smooth Functionals of Covariance Operators
V. Koltchinskii
69
30
0
25 Oct 2017
Sub-Gaussian estimators of the mean of a random vector
Sub-Gaussian estimators of the mean of a random vector
Gábor Lugosi
S. Mendelson
123
172
0
01 Feb 2017
PAC-Bayesian bounds for the Gram matrix and least squares regression
  with a random design
PAC-Bayesian bounds for the Gram matrix and least squares regression with a random design
O. Catoni
46
45
0
16 Mar 2016
Robust dimension-free Gram operator estimates
Robust dimension-free Gram operator estimates
Ilaria Giulini
49
24
0
19 Nov 2015
The lower tail of random quadratic forms, with applications to ordinary
  least squares and restricted eigenvalue properties
The lower tail of random quadratic forms, with applications to ordinary least squares and restricted eigenvalue properties
R. Oliveira
80
101
0
10 Dec 2013
Geometric median and robust estimation in Banach spaces
Geometric median and robust estimation in Banach spaces
Stanislav Minsker
165
311
0
06 Aug 2013
A tail inequality for quadratic forms of subgaussian random vectors
A tail inequality for quadratic forms of subgaussian random vectors
Daniel J. Hsu
Sham Kakade
Tong Zhang
136
420
0
13 Oct 2011
Covariance estimation for distributions with $2+\varepsilon$ moments
Covariance estimation for distributions with 2+ε2+\varepsilon2+ε moments
N. Srivastava
Roman Vershynin
94
117
0
14 Jun 2011
Linear regression through PAC-Bayesian truncation
Linear regression through PAC-Bayesian truncation
Jean-Yves Audibert
O. Catoni
149
16
0
01 Oct 2010
Challenging the empirical mean and empirical variance: a deviation study
Challenging the empirical mean and empirical variance: a deviation study
O. Catoni
161
462
0
10 Sep 2010
Exponential inequalities for self-normalized martingales with
  applications
Exponential inequalities for self-normalized martingales with applications
Bernard Bercu
A. Touati
141
124
0
25 Jul 2007
1