Bounds for the Tracking Error of First-Order Online Optimization Methods
Author
Abstract
Suggested Citation
DOI: 10.1007/s10957-021-01836-9
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Yurii Nesterov, 2018. "Lectures on Convex Optimization," Springer Optimization and Its Applications, Springer, edition 2, number 978-3-319-91578-4, June.
- DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011.
"First-order methods of smooth convex optimization with inexact oracle,"
LIDAM Discussion Papers CORE
2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2014. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Reprints CORE 2594, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Omar Besbes & Yonatan Gur & Assaf Zeevi, 2015. "Non-Stationary Stochastic Optimization," Operations Research, INFORMS, vol. 63(5), pages 1227-1244, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Shota Takahashi & Mituhiro Fukuda & Mirai Tanaka, 2022. "New Bregman proximal type algorithms for solving DC optimization problems," Computational Optimization and Applications, Springer, vol. 83(3), pages 893-931, December.
- A. Scagliotti & P. Colli Franzone, 2022. "A piecewise conservative method for unconstrained convex optimization," Computational Optimization and Applications, Springer, vol. 81(1), pages 251-288, January.
- Xin Jiang & Lieven Vandenberghe, 2022. "Bregman primal–dual first-order method and application to sparse semidefinite programming," Computational Optimization and Applications, Springer, vol. 81(1), pages 127-159, January.
- Liang, Jinpeng & Wu, Jianjun & Gao, Ziyou & Sun, Huijun & Yang, Xin & Lo, Hong K., 2019. "Bus transit network design with uncertainties on the basis of a metro network: A two-step model framework," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 115-138.
- Jueyou Li & Zhiyou Wu & Changzhi Wu & Qiang Long & Xiangyu Wang, 2016. "An Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints," Journal of Optimization Theory and Applications, Springer, vol. 168(1), pages 153-171, January.
- Masaru Ito, 2016. "New results on subgradient methods for strongly convex optimization problems with a unified analysis," Computational Optimization and Applications, Springer, vol. 65(1), pages 127-172, September.
- TAYLOR, Adrien B. & HENDRICKX, Julien M. & François GLINEUR, 2016.
"Exact worst-case performance of first-order methods for composite convex optimization,"
LIDAM Discussion Papers CORE
2016052, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Adrien B. TAYLOR & Julien M. HENDRICKX & François GLINEUR, 2017. "Exact worst-case performance of first-order methods for composite convex optimization," LIDAM Reprints CORE 2875, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Xuexue Zhang & Sanyang Liu & Nannan Zhao, 2023. "An Extended Gradient Method for Smooth and Strongly Convex Functions," Mathematics, MDPI, vol. 11(23), pages 1-14, November.
- Huiyi Cao & Kamil A. Khan, 2023. "General convex relaxations of implicit functions and inverse functions," Journal of Global Optimization, Springer, vol. 86(3), pages 545-572, July.
- Boxiao Chen, 2021. "Data‐Driven Inventory Control with Shifting Demand," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1365-1385, May.
- Masoud Ahookhosh, 2019. "Accelerated first-order methods for large-scale convex optimization: nearly optimal complexity under strong convexity," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(3), pages 319-353, June.
- Julian Rasch & Antonin Chambolle, 2020. "Inexact first-order primal–dual algorithms," Computational Optimization and Applications, Springer, vol. 76(2), pages 381-430, June.
- Francisco García Riesgo & Sergio Luis Suárez Gómez & Enrique Díez Alonso & Carlos González-Gutiérrez & Jesús Daniel Santos, 2021. "Fully Convolutional Approaches for Numerical Approximation of Turbulent Phases in Solar Adaptive Optics," Mathematics, MDPI, vol. 9(14), pages 1-20, July.
- Pavel Shcherbakov & Mingyue Ding & Ming Yuchi, 2021. "Random Sampling Many-Dimensional Sets Arising in Control," Mathematics, MDPI, vol. 9(5), pages 1-16, March.
- Shariat Torbaghan, Shahab & Madani, Mehdi & Sels, Peter & Virag, Ana & Le Cadre, Hélène & Kessels, Kris & Mou, Yuting, 2021. "Designing day-ahead multi-carrier markets for flexibility: Models and clearing algorithms," Applied Energy, Elsevier, vol. 285(C).
- DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2013. "First-order methods with inexact oracle: the strongly convex case," LIDAM Discussion Papers CORE 2013016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Santiago R. Balseiro & Yonatan Gur, 2019. "Learning in Repeated Auctions with Budgets: Regret Minimization and Equilibrium," Management Science, INFORMS, vol. 65(9), pages 3952-3968, September.
- NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Paul R. Rosenbaum, 2023. "Sensitivity analyses informed by tests for bias in observational studies," Biometrics, The International Biometric Society, vol. 79(1), pages 475-487, March.
- Xue Gao & Xingju Cai & Deren Han, 2020. "A Gauss–Seidel type inertial proximal alternating linearized minimization for a class of nonconvex optimization problems," Journal of Global Optimization, Springer, vol. 76(4), pages 863-887, April.
More about this item
Keywords
Smooth convex optimization; Online optimization; Convergence bound; Nesterov acceleration; Tikhonov regularization;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joptap:v:189:y:2021:i:2:d:10.1007_s10957-021-01836-9. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.