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. 2102.04923
  4. Cited By
Berry--Esseen Bounds for Multivariate Nonlinear Statistics with
  Applications to M-estimators and Stochastic Gradient Descent Algorithms
v1v2 (latest)

Berry--Esseen Bounds for Multivariate Nonlinear Statistics with Applications to M-estimators and Stochastic Gradient Descent Algorithms

9 February 2021
Q. Shao
Zhuohui Zhang
ArXiv (abs)PDFHTML

Papers citing "Berry--Esseen Bounds for Multivariate Nonlinear Statistics with Applications to M-estimators and Stochastic Gradient Descent Algorithms"

15 / 15 papers shown
Title
Statistical Inference for Online Algorithms
Statistical Inference for Online Algorithms
Selina Carter
Arun K Kuchibhotla
62
1
0
22 May 2025
Sharp Gaussian approximations for Decentralized Federated Learning
Sharp Gaussian approximations for Decentralized Federated Learning
Soham Bonnerjee
Sayar Karmakar
Wei Biao Wu
FedML
85
0
0
12 May 2025
Online Covariance Estimation in Nonsmooth Stochastic Approximation
L. Jiang
Abhishek Roy
Krishna Balasubramanian
Damek Davis
Dmitriy Drusvyatskiy
Sen Na
127
1
0
07 Feb 2025
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
Marina Sheshukova
Denis Belomestny
Alain Durmus
Eric Moulines
Alexey Naumov
S. Samsonov
75
1
0
07 Oct 2024
Stochastic Optimization Algorithms for Instrumental Variable Regression
  with Streaming Data
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
Xuxing Chen
Abhishek Roy
Yifan Hu
Krishnakumar Balasubramanian
90
1
0
29 May 2024
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
S. Samsonov
Eric Moulines
Qi-Man Shao
Zhuo-Song Zhang
Alexey Naumov
99
5
0
26 May 2024
High Confidence Level Inference is Almost Free using Parallel Stochastic
  Optimization
High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization
Wanrong Zhu
Zhipeng Lou
Ziyang Wei
Wei Biao Wu
85
3
0
17 Jan 2024
Resampling Stochastic Gradient Descent Cheaply for Efficient Uncertainty
  Quantification
Resampling Stochastic Gradient Descent Cheaply for Efficient Uncertainty Quantification
Henry Lam
Zitong Wang
71
1
0
17 Oct 2023
Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning
Online Estimation and Inference for Robust Policy Evaluation in Reinforcement Learning
Weidong Liu
Jiyuan Tu
Yichen Zhang
Xi Chen
OffRL
123
4
0
04 Oct 2023
Online covariance estimation for stochastic gradient descent under
  Markovian sampling
Online covariance estimation for stochastic gradient descent under Markovian sampling
Abhishek Roy
Krishnakumar Balasubramanian
97
6
0
03 Aug 2023
High-dimensional scaling limits and fluctuations of online least-squares
  SGD with smooth covariance
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Krishnakumar Balasubramanian
Promit Ghosal
Ye He
107
5
0
03 Apr 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Bhavya Agrawalla
Krishnakumar Balasubramanian
Promit Ghosal
109
2
0
20 Feb 2023
Online Statistical Inference for Contextual Bandits via Stochastic
  Gradient Descent
Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent
Xinyu Chen
Zehua Lai
He Li
Yichen Zhang
80
4
0
30 Dec 2022
A universal robustification procedure
A universal robustification procedure
Riccardo Passeggeri
Nancy Reid
76
0
0
14 Jun 2022
Bounds in $L^1$ Wasserstein distance on the normal approximation of
  general M-estimators
Bounds in L1L^1L1 Wasserstein distance on the normal approximation of general M-estimators
François Bachoc
M. Fathi
46
0
0
18 Nov 2021
1