NDLI: Parallel stochastic decomposition algorithms for multi-agent systems

Content Provider	IEEE Xplore Digital Library
Author	Yang Yang Scutari, G. Palomar, D.P.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., State Univ. of New York (SUNY), Buffalo, NY, USA (Scutari, G.) \|\| Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Tech., Hong Kong, China (Yang Yang; Palomar, D.P.)
Abstract	In a stochastic optimization problem, the objective function is given in the form of the expectation with respect to some random variables. In many applications, this expectation cannot be computed accurately (e.g., because the statistics of the random variables are unknown). The common approach followed in the literature to deal with this issue is using stochastic gradient schemes, which however suffer from slow convergence. In this paper, we propose for the first time a class of provably convergent Jacobi best-response algorithms for general nonconvex stochastic sum-utility optimization problems, which arise naturally in the design of wireless multi-user interfering systems. The proposed novel decomposition enables all users to update their optimization variables in parallel by solving a sequence of strongly convex subproblems, one for each user. Finally, we customize our algorithms to solve the stochastic sum rate maximization problem over MIMO interference channels and multiple access channels. Numerical results show that our algorithms are much faster than state-of-the-art stochastic gradient schemes.
Starting Page	180
Ending Page	184
File Size	356121
Page Count	5
File Format	PDF
ISBN	9781467355773
ISSN	19483244
DOI	10.1109/SPAWC.2013.6612036
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-16
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Convergence MIMO Linear programming Gradient methods Approximation algorithms stochastic approximation Multi-agent systems parallel optimization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in