{"id":"https://openalex.org/W4385001562","doi":"https://doi.org/10.48550/arxiv.2307.10594","title":"Exploiting Structure for Optimal Multi-Agent Bayesian Decentralized Estimation","display_name":"Exploiting Structure for Optimal Multi-Agent Bayesian Decentralized Estimation","publication_year":2023,"publication_date":"2023-07-20","ids":{"openalex":"https://openalex.org/W4385001562","doi":"https://doi.org/10.48550/arxiv.2307.10594"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2307.10594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2307.10594","pdf_url":"https://arxiv.org/pdf/2307.10594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2307.10594","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102953954","display_name":"Christopher Funk","orcid":"https://orcid.org/0000-0001-6268-678X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Funk, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001168810","display_name":"Ofer Dagan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dagan, Ofer","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080767310","display_name":"Benjamin Noack","orcid":"https://orcid.org/0000-0001-8996-5738"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Noack, Benjamin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100664008","display_name":"Nisar Ahmed","orcid":"https://orcid.org/0000-0002-7555-5671"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed, Nisar R.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9192000031471252,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5577542781829834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5529077053070068},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5259837508201599},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5144181847572327},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5133713483810425},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.5099257230758667},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.48591819405555725},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4821305274963379},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.4651317000389099},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.41334232687950134},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35571107268333435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12049868702888489},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10420078039169312}],"concepts":[{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5577542781829834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5529077053070068},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5259837508201599},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5144181847572327},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5133713483810425},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5099257230758667},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.48591819405555725},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4821305274963379},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4651317000389099},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.41334232687950134},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35571107268333435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12049868702888489},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10420078039169312},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2307.10594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2307.10594","pdf_url":"https://arxiv.org/pdf/2307.10594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2307.10594","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2307.10594","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2307.10594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2307.10594","pdf_url":"https://arxiv.org/pdf/2307.10594","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385001562.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2108418243","https://openalex.org/W2127804977","https://openalex.org/W164103134","https://openalex.org/W2787352659","https://openalex.org/W2487162673","https://openalex.org/W1970611213","https://openalex.org/W2793211469"],"abstract_inverted_index":{"A":[0],"key":[1],"challenge":[2],"in":[3,75,105],"Bayesian":[4],"decentralized":[5,77],"data":[6,19],"fusion":[7,78],"is":[8,26,50,54,60,116],"the":[9,42,46,58,71,91,106,143,175],"`rumor":[10],"propagation'":[11],"or":[12],"`double":[13],"counting'":[14],"phenomenon,":[15],"where":[16],"previously":[17],"sent":[18],"circulates":[20],"back":[21],"to":[22,44,90,118,142,174],"its":[23],"sender.":[24],"It":[25],"often":[27,61],"addressed":[28],"by":[29,69],"approximate":[30],"methods":[31,132],"like":[32],"covariance":[33],"intersection":[34],"(CI)":[35],"which":[36],"takes":[37],"a":[38,80,111,137,155,165,169],"weighted":[39],"average":[40],"of":[41,101],"estimates":[43],"compute":[45,119],"bound.":[47],"The":[48],"problem":[49],"that":[51,68,94,115,135,162],"this":[52,64],"bound":[53,82,167],"not":[55],"tight,":[56],"i.e.":[57],"estimate":[59,172],"over-conservative.":[62],"In":[63],"paper,":[65],"we":[66],"show":[67,134,161],"exploiting":[70],"probabilistic":[72],"independence":[73],"structure":[74],"multi-agent":[76],"problems":[79],"tighter":[81,166],"can":[83],"be":[84],"found":[85],"using":[86],"(i)":[87],"an":[88,125],"expansion":[89],"CI":[92,108,152],"algorithm":[93,153],"uses":[95],"multiple":[96],"(non-monolithic)":[97],"weighting":[98],"factors":[99],"instead":[100],"one":[102],"(monolithic)":[103],"factor":[104],"original":[107,176],"and":[109,122,133,160,168],"(ii)":[110],"general":[112],"optimization":[113],"scheme":[114],"able":[117],"optimal":[120],"bounds":[121],"fully":[123],"exploit":[124],"arbitrary":[126],"dependency":[127],"structure.":[128],"We":[129,146],"compare":[130],"our":[131,149],"on":[136,154],"simple":[138],"problem,":[139],"they":[140],"converge":[141],"same":[144],"solution.":[145],"then":[147],"test":[148],"new":[150],"non-monolithic":[151],"large-scale":[156],"target":[157],"tracking":[158],"simulation":[159],"it":[163],"achieves":[164],"more":[170],"accurate":[171],"compared":[173],"monolithic":[177],"CI.":[178]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2023-07-22T00:00:00"}