v1v2v3 (latest)

Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality

13 July 2023

Papers citing "Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality"

22 / 22 papers shown

Title
Statistical Inference for Online Algorithms Selina Carter Arun K Kuchibhotla 41 1 0 22 May 2025
Sharp Gaussian approximations for Decentralized Federated Learning Soham Bonnerjee Sayar Karmakar Wei Biao Wu FedML 62 0 0 12 May 2025
Enhancing Stochastic Optimization for Statistical Efficiency Using ROOT-SGD with Diminishing Stepsize Tong Zhang Chris Junchi Li 56 0 0 15 Jul 2024
High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization Wanrong Zhu Zhipeng Lou Ziyang Wei Wei Biao Wu 74 3 0 17 Jan 2024
Fast and Robust Online Inference with Stochastic Gradient Descent via Random Scaling S. Lee Yuan Liao M. Seo Youngki Shin 63 32 0 06 Jun 2021
Statistical Inference for Online Decision Making via Stochastic Gradient Descent Haoyu Chen Wenbin Lu R. Song OffRL 125 27 0 14 Oct 2020
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 97 52 0 14 Jun 2020
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 67 76 0 09 Apr 2020
Online Covariance Matrix Estimation in Stochastic Gradient Descent Wanrong Zhu Xi Chen Wei Biao Wu 99 57 0 10 Feb 2020
Momentum-Based Variance Reduction in Non-Convex SGD Ashok Cutkosky Francesco Orabona ODL 92 410 0 24 May 2019
Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT Andreas Anastasiou Krishnakumar Balasubramanian Murat A. Erdogdu 60 38 0 03 Apr 2019
Tight Analyses for Non-Smooth Stochastic Gradient Descent Nicholas J. A. Harvey Christopher Liaw Y. Plan Sikander Randhawa 57 138 0 13 Dec 2018
Statistical Inference for the Population Landscape via Moment Adjusted Stochastic Gradients Tengyuan Liang Weijie Su 62 21 0 20 Dec 2017
Statistical inference using SGD Tianyang Li Liu Liu Anastasios Kyrillidis Constantine Caramanis FedML 41 38 0 21 May 2017
Statistical Inference for Model Parameters in Stochastic Gradient Descent Xi Chen Jason D. Lee Xin T. Tong Yichen Zhang 70 139 0 27 Oct 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 252 3,226 0 15 Jun 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Deep learning with Elastic Averaging SGD Sixin Zhang A. Choromańska Yann LeCun FedML 98 611 0 20 Dec 2014
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm Deanna Needell Nathan Srebro Rachel A. Ward 159 555 0 21 Oct 2013
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method Simon Lacoste-Julien Mark Schmidt Francis R. Bach 187 261 0 10 Dec 2012
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 162 576 0 08 Dec 2012
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 180 769 0 26 Sep 2011