skip to content
Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms. Revision. Preview this item
ClosePreview this item
Checking...

Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms. Revision.

Author: J N Tsitsiklis; D P Bertsekas; M Athans; MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS.
Publisher: Ft. Belvoir Defense Technical Information Center NOV 1984.
Edition/Format:   Book : English
Database:WorldCat
Summary:
This document presents a model for asynchronous distributed computation and then proceed to analyze the convergence of natural asynchronous distributed versions of a large class of deterministic and stochastic gradient-like algorithms. It is shown that such algorithms retain the desirable convergence properties of their centralized counterparts, provided that the time between consecutive communications between  Read more...
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

 

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Document Type: Book
All Authors / Contributors: J N Tsitsiklis; D P Bertsekas; M Athans; MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS.
OCLC Number: 227635162
Notes: Revision of report dated Jan 84.
Description: 50 p.

Abstract:

This document presents a model for asynchronous distributed computation and then proceed to analyze the convergence of natural asynchronous distributed versions of a large class of deterministic and stochastic gradient-like algorithms. It is shown that such algorithms retain the desirable convergence properties of their centralized counterparts, provided that the time between consecutive communications between processors and communication delays are not too large. Additional keywords: Message processing, Mathematical models, Coefficients. (Author).

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


<http://www.worldcat.org/oclc/227635162>
library:oclcnum"227635162"
library:placeOfPublication
library:placeOfPublication
owl:sameAs<info:oclcnum/227635162>
rdf:typeschema:Book
schema:about
schema:about
schema:about
schema:about
schema:about
schema:about
schema:about
schema:about
schema:about
schema:contributor
schema:contributor
schema:contributor
schema:contributor
schema:datePublished"NOV 1984"
schema:datePublished"1984"
schema:description"This document presents a model for asynchronous distributed computation and then proceed to analyze the convergence of natural asynchronous distributed versions of a large class of deterministic and stochastic gradient-like algorithms. It is shown that such algorithms retain the desirable convergence properties of their centralized counterparts, provided that the time between consecutive communications between processors and communication delays are not too large. Additional keywords: Message processing, Mathematical models, Coefficients. (Author)."@en
schema:exampleOfWork<http://worldcat.org/entity/work/id/137337872>
schema:inLanguage"en"
schema:name"Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms. Revision."@en
schema:numberOfPages"50"
schema:publisher
schema:url

Content-negotiable representations

Close Window

Please sign in to WorldCat 

Don't have an account? You can easily create a free account.