Online Covariance Matrix Estimation in Stochastic Gradient Descent

10 February 2020

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

19 / 19 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 71 5 0 26 May 2024
A Full Adagrad algorithm with O(Nd) operations Antoine Godichon-Baggioni Wei Lu Bruno Portier ODL 95 0 0 03 May 2024
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality Ziyang Wei Wanrong Zhu Wei Biao Wu 65 5 0 13 Jul 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression Bhavya Agrawalla Krishnakumar Balasubramanian Promit Ghosal 55 2 0 20 Feb 2023
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming Sen Na Michael W. Mahoney 50 8 0 27 May 2022
On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration Wenlong Mou C. J. Li Martin J. Wainwright Peter L. Bartlett Michael I. Jordan 54 76 0 09 Apr 2020
A generalization of regularized dual averaging and its dynamics Shih-Kang Chao Guang Cheng 32 18 0 22 Sep 2019
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation Weijie J. Su Yuancheng Zhu 60 38 0 13 Feb 2018
Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients Tengyuan Liang Weijie Su 52 21 0 20 Dec 2017
Statistical Inference for Model Parameters in Stochastic Gradient Descent Xi Chen Jason D. Lee Xin T. Tong Yichen Zhang 62 138 0 27 Oct 2016
Multivariate Output Analysis for Markov chain Monte Carlo Dootika Vats James M. Flegal Galin L. Jones 50 276 0 24 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.7K 150,006 0 22 Dec 2014
A nonstandard empirical likelihood for time series D. Nordman Helle Bunzel S. Lahiri 50 24 0 06 Jan 2014
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) Francis R. Bach Eric Moulines 87 405 0 10 Jun 2013
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 146 574 0 08 Dec 2012
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 164 768 0 26 Sep 2011
Online Learning for Matrix Factorization and Sparse Coding Julien Mairal Francis R. Bach Jean Ponce Guillermo Sapiro 141 2,615 0 01 Aug 2009
Batch means and spectral variance estimators in Markov chain Monte Carlo James M. Flegal Galin L. Jones 76 255 0 11 Nov 2008
Computer-intensive rate estimation, diverging statistics and scanning T. McElroy D. Politis 87 25 0 26 Oct 2007