A primal-dual algorithm for distributed optimization

P. Bianchi; W. Hachem

doi:10.1109/CDC.2014.7040050

A primal-dual algorithm for distributed optimization

P. Bianchi
, W. Hachem

Telecom Paris

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Consider a set of N agents who cooperate to solve the problem infx equation where the convex cost functions (f_n, g_n) are local to the agent n. It is assumed that the functions f_n are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Vu and Condat.

Original language	English
Title of host publication	53rd IEEE Conference on Decision and Control,CDC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4240-4245
Number of pages	6
Edition	February
ISBN (Electronic)	9781479977468
DOIs	https://doi.org/10.1109/CDC.2014.7040050
Publication status	Published - 1 Jan 2014
Event	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States Duration: 15 Dec 2014 → 17 Dec 2014

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Number	February
Volume	2015-February
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Country/Territory	United States
City	Los Angeles
Period	15/12/14 → 17/12/14

Access to Document

10.1109/CDC.2014.7040050

Cite this

Bianchi, P., & Hachem, W. (2014). A primal-dual algorithm for distributed optimization. In 53rd IEEE Conference on Decision and Control,CDC 2014 (February ed., pp. 4240-4245). Article 7040050 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, No. February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2014.7040050

@inproceedings{0caae8fde4564ca8832ec7861a4ea803,

title = "A primal-dual algorithm for distributed optimization",

abstract = "Consider a set of N agents who cooperate to solve the problem infx equation where the convex cost functions (fn, gn) are local to the agent n. It is assumed that the functions fn are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Vu and Condat.",

author = "P. Bianchi and W. Hachem",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 ; Conference date: 15-12-2014 Through 17-12-2014",

year = "2014",

month = jan,

day = "1",

doi = "10.1109/CDC.2014.7040050",

language = "English",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "February",

pages = "4240--4245",

booktitle = "53rd IEEE Conference on Decision and Control,CDC 2014",

edition = "February",

}

Bianchi, P & Hachem, W 2014, A primal-dual algorithm for distributed optimization. in 53rd IEEE Conference on Decision and Control,CDC 2014. February edn, 7040050, Proceedings of the IEEE Conference on Decision and Control, no. February, vol. 2015-February, Institute of Electrical and Electronics Engineers Inc., pp. 4240-4245, 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014, Los Angeles, United States, 15/12/14. https://doi.org/10.1109/CDC.2014.7040050

A primal-dual algorithm for distributed optimization. / Bianchi, P.; Hachem, W.
53rd IEEE Conference on Decision and Control,CDC 2014. February. ed. Institute of Electrical and Electronics Engineers Inc., 2014. p. 4240-4245 7040050 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, No. February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A primal-dual algorithm for distributed optimization

AU - Bianchi, P.

AU - Hachem, W.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Consider a set of N agents who cooperate to solve the problem infx equation where the convex cost functions (fn, gn) are local to the agent n. It is assumed that the functions fn are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Vu and Condat.

AB - Consider a set of N agents who cooperate to solve the problem infx equation where the convex cost functions (fn, gn) are local to the agent n. It is assumed that the functions fn are differentiable and have Lipschitz gradients. In this paper, a primal-dual algorithm for distributively solving this problem is proposed. This algorithm is an instance of a primal-dual algorithm separately introduced by Vu and Condat.

U2 - 10.1109/CDC.2014.7040050

DO - 10.1109/CDC.2014.7040050

M3 - Conference contribution

AN - SCOPUS:84988289989

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 4240

EP - 4245

BT - 53rd IEEE Conference on Decision and Control,CDC 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014

Y2 - 15 December 2014 through 17 December 2014

ER -

A primal-dual algorithm for distributed optimization

Abstract

Publication series

Conference

Access to Document

Fingerprint

Cite this