Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT

3 April 2019

Papers citing "Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT"

17 / 17 papers shown

Title
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 61 5 0 26 May 2024
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning R. Srikant 68 6 0 28 Jan 2024
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality Ziyang Wei Wanrong Zhu Wei Biao Wu 44 5 0 13 Jul 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression Bhavya Agrawalla Krishnakumar Balasubramanian Promit Ghosal 41 2 0 20 Feb 2023
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 65 50 0 14 Jun 2020
Global Non-convex Optimization with Discretized Diffusions Murat A. Erdogdu Lester W. Mackey Ohad Shamir 40 105 0 29 Oct 2018
Deterministic Inequalities for Smooth M-estimators Arun K. Kuchibhotla 40 8 0 13 Sep 2018
Asymptotic Optimality in Stochastic Optimization John C. Duchi Feng Ruan 34 62 0 16 Dec 2016
Measuring Sample Quality with Diffusions Jackson Gorham Andrew B. Duncan Sandra Jeanne Vollmer Lester W. Mackey 55 116 0 21 Nov 2016
Statistical Inference for Model Parameters in Stochastic Gradient Descent Xi Chen Jason D. Lee Xin T. Tong Yichen Zhang 49 137 0 27 Oct 2016
Assessing the multivariate normal approximation of the maximum likelihood estimator from high-dimensional, heterogeneous data Andreas Anastasiou 18 13 0 13 Oct 2015
Convergence rates of sub-sampled Newton methods Murat A. Erdogdu Andrea Montanari 55 157 0 12 Aug 2015
Central Limit Theorems and Bootstrap in High Dimensions Victor Chernozhukov Denis Chetverikov Kengo Kato 43 312 0 11 Dec 2014
Non-parametric Stochastic Approximation with Large Step sizes Aymeric Dieuleveut Francis R. Bach 37 169 0 02 Aug 2014
Hypothesis testing by convex optimization A. Goldenshluger A. Juditsky A. Nemirovski 40 26 0 26 Nov 2013
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 76 764 0 26 Sep 2011
On the rate of convergence in the martingale central limit theorem J. Mourrat 59 36 0 25 Mar 2011