Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Convergence of Limited Communication Gradient Methods
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH - Royal Institute of Technology.ORCID iD: 0000-0002-6617-8683
KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.ORCID iD: 0000-0001-9810-3478
Show others and affiliations
2018 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523Article in journal (Refereed) Accepted
Abstract [en]

Distributed optimization increasingly plays a centralrole in economical and sustainable operation of cyber-physicalsystems. Nevertheless, the complete potential of the technologyhas not yet been fully exploited in practice due to communicationlimitations posed by the real-world infrastructures. This workinvestigates fundamental properties of distributed optimizationbased on gradient methods, where gradient information iscommunicated using limited number of bits. In particular, ageneral class of quantized gradient methods are studied wherethe gradient direction is approximated by a finite quantizationset. Sufficient and necessary conditions are provided on sucha quantization set to guarantee that the methods minimize anyconvex objective function with Lipschitz continuous gradient anda nonempty and bounded set of optimizers. A lower bound on thecardinality of the quantization set is provided, along with specificexamples of minimal quantizations. Convergence rate results areestablished that connect the fineness of the quantization andthe number of iterations needed to reach a predefined solutionaccuracy. Generalizations of the results to a relevant class ofconstrained problems using projections are considered. Finally,the results are illustrated by simulations of practical systems.

Place, publisher, year, edition, pages
IEEE Press, 2018.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223650OAI: oai:DiVA.org:kth-223650DiVA, id: diva2:1185971
Note

QC 20180412

Available from: 2018-02-27 Created: 2018-02-27 Last updated: 2018-04-12Bibliographically approved

Open Access in DiVA

fulltext(3646 kB)4 downloads
File information
File name FULLTEXT01.pdfFile size 3646 kBChecksum SHA-512
61aed6dc4d0dddb7aea9408322f838f3182c896158ffe004db4a03fd792ed6f915862a0f437c6409110ea162bc26575c0606a8de56f0da556e12fdc7413dc21f
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Magnusson, SindriCarlo, Fischione
By organisation
Network and Systems engineering
In the same journal
IEEE Transactions on Automatic Control
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 4 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 28 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf