Recent Theoretical Advances in Decentralized Distributed Convex Optimization

Eduard Gorbunov (), Alexander Rogozin (), Aleksandr Beznosikov (), Darina Dvinskikh () and Alexander Gasnikov ()
Additional contact information
Eduard Gorbunov: Moscow Institute of Physics and Technology
Alexander Rogozin: Moscow Institute of Physics and Technology
Aleksandr Beznosikov: Moscow Institute of Physics and Technology
Darina Dvinskikh: Moscow Institute of Physics and Technology
Alexander Gasnikov: Moscow Institute of Physics and Technology

A chapter in High-Dimensional Optimization and Probability, 2022, pp 253-325 from Springer

Abstract: Abstract In the last few years, the theory of decentralized distributed convex optimization has made significant progress. The lower bounds on communications rounds and oracle calls have appeared, as well as methods that reach both of these bounds. In this paper, we focus on how these results can be explained based on optimal algorithms for the non-distributed setup. In particular, we provide our recent results that have not been published yet and that could be found in detail only in arXiv preprints.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (2)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-00832-0_8

Ordering information: This item can be ordered from
http://www.springer.com/9783031008320

DOI: 10.1007/978-3-031-00832-0_8

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().