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Decentralized Approximate Bayesian Inference for Distributed Sensor Network

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TypeOfResource
Text
TitleInfo
Title
Decentralized Approximate Bayesian Inference for Distributed Sensor Network
Name (type = personal)
NamePart (type = family)
Babagholami Mohamadabad
NamePart (type = given)
Behnam
Affiliation
Computer Science (New Brunswick), Rutgers University
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Yoon
NamePart (type = given)
Sejong
Affiliation
Computer Science (New Brunswick), Rutgers University
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Pavlovic
NamePart (type = given)
Vladimir
Affiliation
Computer Science (New Brunswick), Rutgers University
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (authority = RutgersOrg-Department); (type = corporate)
NamePart
Computer Science (New Brunswick)
Name (authority = RutgersOrg-School); (type = corporate)
NamePart
School of Arts and Sciences (SAS) (New Brunswick)
Genre (authority = RULIB-FS)
Conference Paper or Lecture
Genre (authority = NISO JAV)
Accepted Manuscript (AM)
Note (type = peerReview)
Peer reviewed
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
2015
Abstract (type = Abstract)
Bayesian models provide a framework for probabilistic modelling of complex datasets. Many such models are computationally demanding, especially in the presence of large datasets. In sensor network applications, statistical (Bayesian) parameter estimation usually relies on decentralized algorithms, in which both data and computation are distributed across the nodes of the network. In this paper we propose a framework for decentralized Bayesian learning using Bregman Alternating Direction Method of Multipliers (B-ADMM).We demonstrate the utility of our framework, with Mean Field Variational Bayes (MFVB) as the primitive for distributed affine structure from motion (SfM).
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
PhysicalDescription
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application/pdf
Extent
7 p.
Extension
DescriptiveEvent
Type
Citation
AssociatedObject
Name
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence and the Twenty-Eighth Innovative Applications of Artificial Intelligence Conference
Type
Journal
Relationship
Has part
Reference (type = url)
http://www.aaai.org/Press/Proceedings/aaai16.php
DateTime (encoding = w3cdtf)
2016
AssociatedEntity
Role
Publisher
Name
Association for the Advancement of Artificial Intelligence
Extension
DescriptiveEvent
Type
Conference
Label
AAAI-16: 30th AAAI Conference on Artificial Intelligence
Place
Phoenix, AZ
DateTime (encoding = w3cdtf)
2016-02
AssociatedEntity
Role
Sponsor
Name
Association for the Advancement of Artificial Intelligence
RelatedItem (type = host)
TitleInfo
Title
Babagholami Mohamadabad, Behnam
Identifier (type = local)
rucore30181600001
RelatedItem (type = host)
TitleInfo
Title
Pavlovic, Vladimir
Identifier (type = local)
rucore30181300001
Subject (authority = LCSH)
Topic
Artificial intelligence
Subject (authority = LCSH)
Topic
Bayesian statistical decision theory
Subject (authority = LCSH)
Topic
Sensor networks
Subject (authority = local)
Topic
Bregman Alternating Direction Method of Multipliers
RelatedItem (type = host)
TitleInfo
Title
Yoon, Sejong
Identifier (type = local)
rucore30177400001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3CN75TJ
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Rights

RightsDeclaration (AUTHORITY = FS); (ID = rulibRdec0004)
Copyright for scholarly resources published in RUcore is retained by the copyright holder. By virtue of its appearance in this open access medium, you are free to use this resource, with proper attribution, in educational and other non-commercial settings. Other uses, such as reproduction or republication, may require the permission of the copyright holder.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsEvent
Type
Permission or license
AssociatedObject
Type
License
Name
Multiple author license v. 1
Detail
I hereby grant to Rutgers, The State University of New Jersey (Rutgers) the non-exclusive right to retain, reproduce, and distribute the deposited work (Work) in whole or in part, in and from its electronic format, without fee. This agreement does not represent a transfer of copyright to Rutgers.Rutgers may make and keep more than one copy of the Work for purposes of security, backup, preservation, and access and may migrate the Work to any medium or format for the purpose of preservation and access in the future. Rutgers will not make any alteration, other than as allowed by this agreement, to the Work.I represent and warrant to Rutgers that the Work is my original work. I also represent that the Work does not, to the best of my knowledge, infringe or violate any rights of others.I further represent and warrant that I have obtained all necessary rights to permit Rutgers to reproduce and distribute the Work and that any third-party owned content is clearly identified and acknowledged within the Work.By granting this license, I acknowledge that I have read and agreed to the terms of this agreement and all related RUcore and Rutgers policies.
RightsEvent
Type
Embargo
DateTime (encoding = w3cdtf); (point = start)
2015-12-04
DateTime (point = end); (encoding = w3cdtf)
2016-02-28
Detail
Access to this PDF is restricted in accordance with the policies of AAAI, which permits only limited distribution prior to AAAI publication. Access to this version will be made available following the AAAI Conference in February 2016.
RightsEvent
Type
Permissions research
DateTime (encoding = w3cdtf)
2015-12-03
Detail
Author's toolkit here: http://www.aaai.org/Conferences/AAAI/2016/aaai16call.php. Copyright form allows author to post on employer's own web page or ftp site, but only limited distribution of the article/paper prior to publication. Distribution license grants AAAI nonexclusive rights to use the work.
AssociatedEntity
Role
Cataloger
Name
Rhonda Marker
RightsHolder (type = corporate)
Name
Association for the Advancement of Artificial Intelligence
Role
Copyright holder
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RULTechMD (ID = TECHNICAL1)
ContentModel
Document
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