Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Asynchronous incremental block-coordinate descent
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-1725-2901
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.
2014 (English)In: 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), IEEE conference proceedings, 2014, 19-24 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper studies a flexible algorithm for minimizing a sum of component functions, each of which depends on a large number of decision variables. Such formulations appear naturally in “big data” applications, where each function describes the loss estimated using the data available at a specific machine, and the number of features under consideration is huge. In our algorithm, a coordinator updates a global iterate based on delayed partial gradients of the individual objective functions with respect to blocks of coordinates. Delayed incremental gradient and delayed coordinate descent algorithms are obtained as special cases. Under the assumption of strong convexity and block coordinate-wise Lipschitz continuous partial gradients, we show that the algorithm converges linearly to a ball around the optimal value. Contrary to related proposals in the literature, our algorithm is delay-insensitive: it converges for any bounded information delay, and its step-size parameter can be chosen independently of the maximum delay bound.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2014. 19-24 p.
Keyword [en]
Big Data, gradient methods, asynchronous incremental block-coordinate descent, big data applications, block coordinate-wise Lipschitz continuous partial gradients;bounded information delay, component function sum minimization, delayed partial gradients, global iterate, maximum delay bound, step-size parameter, Algorithm design and analysis, Color, Convergence, Delays, Servers, Standards, Vectors
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-164288DOI: 10.1109/ALLERTON.2014.7028430Scopus ID: 2-s2.0-84946692347OAI: oai:DiVA.org:kth-164288DiVA: diva2:805300
Conference
52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton),Sept. 30 2014-Oct. 3 2014,Monticello, IL
Note

QC 20150511

Available from: 2015-04-15 Created: 2015-04-15 Last updated: 2015-05-11Bibliographically approved

Open Access in DiVA

fulltext(851 kB)94 downloads
File information
File name FULLTEXT01.pdfFile size 851 kBChecksum SHA-512
2bf4d04444de0e488e81a7464e17e2ec32d552fa209b8b94823a7364be2cde5e05a9f365489c859963245cf93f3d8fa74acd84a8a43ee5673b2c15cc699ee6dc
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusIEEEXplore

Authority records BETA

Aytekin, Arda

Search in DiVA

By author/editor
Aytekin, ArdaFeyzmahdavian, Hamid RezaJohansson, Mikael
By organisation
Automatic Control
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 94 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

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 149 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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