v1v2v3 (latest)

Online Covariance Matrix Estimation in Stochastic Gradient Descent

Journal of the American Statistical Association (JASA), 2020

10 February 2020

Papers citing "Online Covariance Matrix Estimation in Stochastic Gradient Descent"

36 / 36 papers shown

$Statistical Inference for Linear Functionals of Online Least-squares SGD when $t \gtrsim d^{1+δ}$$

Statistical Inference for Linear Functionals of Online Least-squares SGD when

t \gtrsim d^{1+δ}

Bhavya Agrawalla

Krishnakumar Balasubramanian

Promit Ghosal

130

22 Oct 2025

Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation

140

14 Oct 2025

Beyond Sin-Squared Error: Linear-Time Entrywise Uncertainty Quantification for Streaming PCAConference on Uncertainty in Artificial Intelligence (UAI), 2025

Syamantak Kumar

Shourya Pandey

Purnamrita Sarkar

247

14 Jun 2025

Statistical Inference for Online Algorithms

Selina Carter

Arun K Kuchibhotla

315

22 May 2025

Smoothed SGD for quantiles: Bahadur representation and Gaussian approximation

Likai Chen

Georg Keilbar

Wei Biao Wu

211

19 May 2025

Sharp Gaussian approximations for Decentralized Federated Learning

392

12 May 2025

Central Limit Theorems for Stochastic Gradient Descent Quantile Estimators

389

04 Mar 2025

Online Covariance Estimation in Nonsmooth Stochastic ApproximationAnnual Conference Computational Learning Theory (COLT), 2025

L. Jiang

Abhishek Roy

Krishna Balasubramanian

Damek Davis

Dmitriy Drusvyatskiy

Sen Na

346

07 Feb 2025

Asymptotic Time-Uniform Inference for Parameters in Averaged Stochastic Approximation

228

19 Oct 2024

Enhancing Stochastic Optimization for Statistical Efficiency Using ROOT-SGD with Diminishing Stepsize

Tong Zhang

Chris Junchi Li

396

15 Jul 2024

Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

Xuxing Chen

Abhishek Roy

Yifan Hu

Krishnakumar Balasubramanian

292

29 May 2024

Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning

405

26 May 2024

Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent

Holger Dette

Carina Graw

243

21 May 2024

A Full Adagrad algorithm with O(Nd) operations

Antoine Godichon-Baggioni

Wei Lu

Bruno Portier

ODL

345

03 May 2024

A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques

...

225

17 Mar 2024

High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization

286

17 Jan 2024

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference

D. Huo

Yudong Chen

Qiaomin Xie

228

18 Dec 2023

SGMM: Stochastic Approximation to Generalized Method of Moments

247

25 Aug 2023

Online covariance estimation for stochastic gradient descent under Markovian sampling

Abhishek Roy

Krishnakumar Balasubramanian

371

03 Aug 2023

Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality

Ziyang Wei

Wanrong Zhu

Wei Biao Wu

392

13 Jul 2023

A Central Limit Theorem for Algorithmic Estimator of Saddle Point

Abhishek Roy

Yian Ma

406

09 Jun 2023

Acceleration of stochastic gradient descent with momentum by averaging: finite-sample rates and asymptotic normality

235

28 May 2023

Fairness Uncertainty Quantification: How certain are you that the model is fair?

Abhishek Roy

P. Mohapatra

210

27 Apr 2023

On the Utility of Equal Batch Sizes for Inference in Stochastic Gradient Descent

Rahul Singh

A. Shukla

Dootika Vats

249

14 Mar 2023

Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression

Bhavya Agrawalla

Krishnakumar Balasubramanian

Promit Ghosal

519

20 Feb 2023

Online Statistical Inference for Contextual Bandits via Stochastic Gradient Descent

Zhihong Liu

Yichen Zhang

266

30 Dec 2022

Covariance Estimators for the ROOT-SGD Algorithm in Online Learning

Yiling Luo

X. Huo

Y. Mei

179

02 Dec 2022

Fast Inference for Quantile Regression with Tens of Millions of ObservationsSocial Science Research Network (SSRN), 2022

682

29 Sep 2022

Parameter-Parallel Distributed Variational Quantum AlgorithmSciPost Physics (SciPost Phys.), 2022

208

31 Jul 2022

Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming

Sen Na

Michael W. Mahoney

476

27 May 2022

A Statistical Analysis of Polyak-Ruppert Averaged Q-learningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021

Wenhao Yang

448

29 Dec 2021

An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear Regression ModelsJournal of Computational And Graphical Statistics (JCGS), 2021

287

02 Nov 2021

Statistical Estimation and Inference via Local SGD in Federated Learning

186

03 Sep 2021

Fast and Robust Online Inference with Stochastic Gradient Descent via Random ScalingAAAI Conference on Artificial Intelligence (AAAI), 2021

323

06 Jun 2021

Online Statistical Inference for Stochastic Optimization via Kiefer-Wolfowitz MethodsJournal of the American Statistical Association (JASA), 2021

437

05 Feb 2021

Asymptotic Analysis of Conditioned Stochastic Gradient Descent

Rémi Leluc

Franccois Portier

342

04 Jun 2020