Linear Convergence of Adaptive Stochastic Gradient Descent

28 August 2019

Papers citing "Linear Convergence of Adaptive Stochastic Gradient Descent"

11 / 11 papers shown

Title
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad Sayantan Choudhury N. Tupitsa Nicolas Loizou Samuel Horváth Martin Takáč Eduard A. Gorbunov 43 1 0 05 Mar 2024
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization Anthony Bardou Patrick Thiran Thomas Begin 24 4 0 31 May 2023
TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization Xiang Li Junchi Yang Niao He 34 8 0 31 Oct 2022
Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G. Zhang Hong-Ming Chiu Richard Y. Zhang 27 10 0 24 Aug 2022
Improved Policy Optimization for Online Imitation Learning J. Lavington Sharan Vaswani Mark Schmidt OffRL 28 6 0 29 Jul 2022
Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization Junchi Yang Xiang Li Niao He ODL 45 22 0 01 Jun 2022
Optimal Algorithms for Stochastic Multi-Level Compositional Optimization Wei Jiang Bokun Wang Yibo Wang Lijun Zhang Tianbao Yang 81 17 0 15 Feb 2022
Stochastic gradient descent with noise of machine learning type. Part I: Discrete time analysis Stephan Wojtowytsch 25 50 0 04 May 2021
Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes Steffen Dereich Sebastian Kassing 34 27 0 16 Feb 2021
Sequential convergence of AdaGrad algorithm for smooth convex optimization Cheik Traoré Edouard Pauwels 14 21 0 24 Nov 2020
A Qualitative Study of the Dynamic Behavior for Adaptive Gradient Algorithms Chao Ma Lei Wu E. Weinan ODL 19 23 0 14 Sep 2020