NON-ERGODIC LINEAR CONVERGENCE PROPERTY OF THE DELAYED GRADIENT DESCENT UNDER THE STRONGLY CONVEXITY AND THE POLYAK-LOJASIEWICZ CONDITION

被引：0

作者：

Choi, Hyung Jun ^{[1
]}

Choi, Woocheol ^{[2
]}

Seok, Jinmyoung ^{[3
]}

机构：

[1] School of Liberal Arts, Korea University of Technology and Education, Cheonan,31253, Korea, Republic of

[2] Department of Mathematics, Sungkyunkwan University, Suwon,16419, Korea, Republic of

[3] Department of Mathematics Education, Seoul National University, Seoul,08826, Korea, Republic of

来源：

arXiv | 2023年

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Convex optimization - Cost benefit analysis - Cost estimating - Cost functions - Gradient methods - Learning algorithms - Stochastic systems - Timing circuits

引用

共 10 条

[1] Non-ergodic linear convergence property of the delayed gradient descent under the strongly convexity and the Polyak-Lojasiewicz condition
Choi, Hyung Jun
Choi, Woocheol
Seok, Jinmyoung
ANALYSIS AND APPLICATIONS, 2024, 22 (06) : 1023 - 1051
[2] Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Lojasiewicz Condition
Fan, Chen
Thrampoulidis, Christos
Schmidt, Mark
arXiv, 2023,
[3] Fast Convergence of Random Reshuffling Under Over-Parameterization and the Polyak-Lojasiewicz Condition
Fan, Chen
Thrampoulidis, Christos
Schmidt, Mark
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES: RESEARCH TRACK, ECML PKDD 2023, PT IV, 2023, 14172 : 301 - 315
[4] Online Stochastic Gradient Methods Under Sub-Weibull Noise and the Polyak-Lojasiewicz Condition
Kim, Seunghyun
Madden, Liam
Dall'Anese, Emiliano
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), 2022, : 3499 - 3506
[5] Convergence rates for the heavy-ball continuous dynamics for non-convex optimization, under Polyak-Lojasiewicz condition
Apidopoulos, Vassilis
Ginatta, Nicolo
Villa, Silvia
JOURNAL OF GLOBAL OPTIMIZATION, 2022, 84 (03) : 563 - 589
[6] Online Stochastic Gradient Methods Under Sub-Weibull Noise and the Polyak-Lojasiewicz Condition
University of Colorado, Department of Applied Mathematics, Boulder, United States
不详
Proc IEEE Conf Decis Control, 2022, (3499-3506):
[7] Quantized Zeroth-Order Gradient Tracking Algorithm for Distributed Nonconvex Optimization Under Polyak-Lojasiewicz Condition
Xu, Lei
Yi, Xinlei
Deng, Chao
Shi, Yang
Chai, Tianyou
Yang, Tao
IEEE TRANSACTIONS ON CYBERNETICS, 2024, 54 (10) : 5746 - 5758
[8] Convergence of stochastic gradient descent under a local Lojasiewicz condition for deep neural networks
An, Jing
Lu, Jianfeng
arXiv, 2023,
[9] Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness
Scaman, Kevin
Malherbe, Cédric
Dos Santos, Ludovic
Proceedings of Machine Learning Research, 2022, 162 : 19310 - 19327
[10] Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness
Scaman, Kevin
Malherbe, Cedric
Dos Santos, Ludovic
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 162, 2022, : 19310 - 19327

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