An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias

14 June 2020

Lu Yu

Krishnakumar Balasubramanian

S. Volgushev

Murat A. Erdogdu

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Papers citing "An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias"

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A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 24 0 0 11 Apr 2025
Online Inference for Quantiles by Constant Learning-Rate Stochastic Gradient Descent Ziyang Wei Jiaqi Li Likai Chen W. Wu 46 0 0 04 Mar 2025
Coupling-based Convergence Diagnostic and Stepsize Scheme for Stochastic Gradient Descent Xiang Li Qiaomin Xie 76 0 0 15 Dec 2024
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way Jeongyeol Kwon Luke Dotson Yudong Chen Qiaomin Xie 28 1 0 16 Oct 2024
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation Marina Sheshukova Denis Belomestny Alain Durmus Eric Moulines Alexey Naumov S. Samsonov 33 1 0 07 Oct 2024
Enhancing Stochastic Optimization for Statistical Efficiency Using ROOT-SGD with Diminishing Stepsize Tong Zhang Chris Junchi Li 36 0 0 15 Jul 2024
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise Sebastian Allmeier Nicolas Gast 36 5 0 23 May 2024
Uncertainty quantification by block bootstrap for differentially private stochastic gradient descent Holger Dette Carina Graw 18 0 0 21 May 2024
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA Yixuan Zhang D. Huo Yudong Chen Qiaomin Xie 27 2 0 09 Apr 2024
A Selective Review on Statistical Methods for Massive Data Computation: Distributed Computing, Subsampling, and Minibatch Techniques Xuetong Li Yuan Gao Hong Chang Danyang Huang Yingying Ma ... Ke Xu Jing Zhou Xuening Zhu Yingqiu Zhu Hansheng Wang 36 7 0 17 Mar 2024
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation Yixuan Zhang Qiaomin Xie 27 4 0 25 Jan 2024
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference D. Huo Yudong Chen Qiaomin Xie 32 4 0 18 Dec 2023
Demystifying the Myths and Legends of Nonconvex Convergence of SGD Aritra Dutta El Houcine Bergou Soumia Boucherouite Nicklas Werge M. Kandemir Xin Li 26 0 0 19 Oct 2023
Robust Stochastic Optimization via Gradient Quantile Clipping Ibrahim Merad Stéphane Gaïffas 16 1 0 29 Sep 2023
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning Nikhil Ghosh Spencer Frei Wooseok Ha Ting Yu MLT 30 3 0 06 Aug 2023
Online covariance estimation for stochastic gradient descent under Markovian sampling Abhishek Roy Krishnakumar Balasubramanian 24 5 0 03 Aug 2023
Weighted Averaged Stochastic Gradient Descent: Asymptotic Normality and Optimality Ziyang Wei Wanrong Zhu W. Wu 17 3 0 13 Jul 2023
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements Emmanouil-Vasileios Vlatakis-Gkaragkounis Angeliki Giannou Yudong Chen Qiaomin Xie 24 4 0 28 Jun 2023
Convergence and concentration properties of constant step-size SGD through Markov chains Ibrahim Merad Stéphane Gaïffas 36 5 0 20 Jun 2023
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator Haobo Qi Feifei Wang Hansheng Wang 17 13 0 13 Apr 2023
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance Krishnakumar Balasubramanian Promit Ghosal Ye He 28 5 0 03 Apr 2023
Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality Alireza Mousavi-Hosseini Tyler Farghly Ye He Krishnakumar Balasubramanian Murat A. Erdogdu 42 25 0 07 Mar 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression Bhavya Agrawalla Krishnakumar Balasubramanian Promit Ghosal 23 2 0 20 Feb 2023
Why is parameter averaging beneficial in SGD? An objective smoothing perspective Atsushi Nitanda Ryuhei Kikuchi Shugo Maeda Denny Wu FedML 18 0 0 18 Feb 2023
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes D. Huo Yudong Chen Qiaomin Xie 18 17 0 03 Oct 2022
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 319 48 0 29 Sep 2022
Two-Tailed Averaging: Anytime, Adaptive, Once-in-a-While Optimal Weight Averaging for Better Generalization Gábor Melis MoMe 19 1 0 26 Sep 2022
$Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers$ Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$ -Covers Sejun Park Umut Simsekli Murat A. Erdogdu 43 9 0 19 Sep 2022
On Uniform Boundedness Properties of SGD and its Momentum Variants Xiaoyu Wang M. Johansson 18 3 0 25 Jan 2022
Non-Asymptotic Analysis of Online Multiplicative Stochastic Gradient Descent Riddhiman Bhattacharya Tiefeng Jiang 8 0 0 14 Dec 2021
Stochastic Gradient Line Bayesian Optimization for Efficient Noise-Robust Optimization of Parameterized Quantum Circuits Shiro Tamiya H. Yamasaki 13 24 0 15 Nov 2021
Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization Zaiwei Chen Shancong Mou S. T. Maguluri 17 13 0 11 Nov 2021
Bootstrapping the error of Oja's algorithm Robert Lunde Purnamrita Sarkar Rachel A. Ward 11 10 0 28 Jun 2021
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms A. Camuto George Deligiannidis Murat A. Erdogdu Mert Gurbuzbalaban Umut cSimcsekli Lingjiong Zhu 23 29 0 09 Jun 2021
Learning Curves for SGD on Structured Features Blake Bordelon C. Pehlevan MLT 15 0 0 04 Jun 2021
Manipulating SGD with Data Ordering Attacks Ilia Shumailov Zakhar Shumaylov Dmitry Kazhdan Yiren Zhao Nicolas Papernot Murat A. Erdogdu Ross J. Anderson AAML 112 90 0 19 Apr 2021
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance Hongjian Wang Mert Gurbuzbalaban Lingjiong Zhu Umut cSimcsekli Murat A. Erdogdu 13 41 0 20 Feb 2021
Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm Yanhao Jin Tesi Xiao Krishnakumar Balasubramanian 13 5 0 10 Feb 2021
Stochastic Multi-level Composition Optimization Algorithms with Level-Independent Convergence Rates Krishnakumar Balasubramanian Saeed Ghadimi A. Nguyen 14 33 0 24 Aug 2020
Convergence of Langevin Monte Carlo in Chi-Squared and Renyi Divergence Murat A. Erdogdu Rasa Hosseinzadeh Matthew Shunshi Zhang 86 41 0 22 Jul 2020
On the Convergence of Langevin Monte Carlo: The Interplay between Tail Growth and Smoothness Murat A. Erdogdu Rasa Hosseinzadeh 6 74 0 27 May 2020
Error Lower Bounds of Constant Step-size Stochastic Gradient Descent Zhiyan Ding Yiding Chen Qin Li Xiaojin Zhu 17 4 0 18 Oct 2019
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 124 1,198 0 16 Aug 2016