Modified Fejér sequences and applications
Name
10589_2017_9962_ReferencePDF.pdf
Size
193.16 KB
Format
Adobe PDF
Checksum (MD5)
1be2adc6342d926ed5434f51aeaca089
Author(s)
Lin, Junhong
Rosasco, Lorenzo
Villa, Silvia
Zhou, Ding-Xuan
Date Issued
November 2017
Journal
Computational Optimization and Applications
Publisher
Springer US
Citation
Lin, Junhong, et al. “Modified Fejér Sequences and Applications.” Computational Optimization and Applications, vol. 71, no. 1, Sept. 2018, pp. 95–113.
Version
Author's final manuscript
Abstract
In this note, we propose and study the notion of modified Fejér sequences. Within a Hilbert space setting, this property has been used to prove ergodic convergence of proximal incremental subgradient methods. Here we show that indeed it provides a unifying framework to prove convergence rates for objective function values of several optimization algorithms. In particular, our results apply to forward–backward splitting algorithm, incremental subgradient proximal algorithm, and the Douglas–Rachford splitting method including and generalizing known results.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/s10589-017-9962-1
