{"id":"https://openalex.org/W4289655163","doi":"https://doi.org/10.1109/isit50566.2022.9834859","title":"Local Limit Theorems for Approximate Maximum Likelihood Estimation of Network Information Spreading Models","display_name":"Local Limit Theorems for Approximate Maximum Likelihood Estimation of Network Information Spreading Models","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655163","doi":"https://doi.org/10.1109/isit50566.2022.9834859"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834859","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004115333","display_name":"Abram Magner","orcid":"https://orcid.org/0000-0002-3082-9915"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abram Magner","raw_affiliation_strings":["University at Albany,Department of Computer Science,Albany,NY,USA","Department of Computer Science, University at Albany, Albany, NY, USA"],"affiliations":[{"raw_affiliation_string":"University at Albany,Department of Computer Science,Albany,NY,USA","institution_ids":["https://openalex.org/I392282"]},{"raw_affiliation_string":"Department of Computer Science, University at Albany, Albany, NY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090940496","display_name":"Amith Kumar Singh","orcid":"https://orcid.org/0009-0006-0835-2037"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amith Kumar Singh","raw_affiliation_strings":["University at Albany,Department of Computer Science,Albany,NY,USA","Department of Computer Science, University at Albany, Albany, NY, USA"],"affiliations":[{"raw_affiliation_string":"University at Albany,Department of Computer Science,Albany,NY,USA","institution_ids":["https://openalex.org/I392282"]},{"raw_affiliation_string":"Department of Computer Science, University at Albany, Albany, NY, USA","institution_ids":["https://openalex.org/I392282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004115333"],"corresponding_institution_ids":["https://openalex.org/I392282"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12382739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1671","last_page":"1676"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11896","display_name":"Opportunistic and Delay-Tolerant Networks","score":0.982200026512146,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/likelihood-function","display_name":"Likelihood function","score":0.6607290506362915},{"id":"https://openalex.org/keywords/central-limit-theorem","display_name":"Central limit theorem","score":0.6014712452888489},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5827083587646484},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.5668586492538452},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5453940033912659},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.52801913022995},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4960571229457855},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4754240810871124},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.46275943517684937},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4621494710445404},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.4521428048610687},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4487544000148773},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4235348701477051},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.420273095369339},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.41423988342285156},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.41188061237335205},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38857316970825195},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3863624930381775},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2226930558681488}],"concepts":[{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.6607290506362915},{"id":"https://openalex.org/C166785042","wikidata":"https://www.wikidata.org/wiki/Q190391","display_name":"Central limit theorem","level":2,"score":0.6014712452888489},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5827083587646484},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.5668586492538452},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5453940033912659},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.52801913022995},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4960571229457855},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4754240810871124},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.46275943517684937},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4621494710445404},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.4521428048610687},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4487544000148773},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4235348701477051},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.420273095369339},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.41423988342285156},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.41188061237335205},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38857316970825195},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3863624930381775},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2226930558681488},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834859","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834859","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W186403072","https://openalex.org/W1577200065","https://openalex.org/W2013563471","https://openalex.org/W2057340373","https://openalex.org/W2061820396","https://openalex.org/W2149734713","https://openalex.org/W2528080966","https://openalex.org/W2963597852","https://openalex.org/W3178213531","https://openalex.org/W3190934389","https://openalex.org/W6682086128","https://openalex.org/W6713469395"],"related_works":["https://openalex.org/W4388397594","https://openalex.org/W2356093187","https://openalex.org/W164417758","https://openalex.org/W2898901530","https://openalex.org/W2186819079","https://openalex.org/W4287728430","https://openalex.org/W4233488282","https://openalex.org/W2794631075","https://openalex.org/W3040609822","https://openalex.org/W2783892006"],"abstract_inverted_index":{"We":[0,92,113],"consider":[1],"infection/spreading":[2],"process":[3],"models":[4,36],"on":[5,121],"a":[6,24,52,64,72,81,102,118],"graph":[7],"in":[8],"which":[9],"infected":[10,63,87],"nodes":[11],"are":[12],"associated":[13,44],"with":[14,76,107],"real-valued":[15],"messages":[16,45],"that":[17,57,62,94,116,141],"evolve":[18],"as":[19,51,80],"they":[20],"spread,":[21],"according":[22],"to":[23,71,132],"parametric":[25],"probabilistic":[26],"message":[27],"spreading":[28],"model.":[29],"Estimation":[30],"of":[31,34,54,60,83,86,89,126,135,153],"the":[32,55,58,84,95,122,124,127,133,136,150,154],"parameters":[33],"such":[35],"from":[37],"an":[38],"observed":[39],"sample":[40],"infection":[41],"trajectory":[42],"and":[43,48,110],"presents":[46],"computational":[47,111],"statistical":[49],"challenges":[50],"result":[53],"fact":[56],"set":[59],"neighbors":[61,88],"given":[65],"node":[66],"is":[67,130],"unobserved.":[68],"This":[69],"leads":[70],"log":[73,96,138,155],"likelihood":[74,97,142],"function":[75,82,129],"exponentially":[77],"many":[78],"terms":[79],"number":[85],"each":[90],"node.":[91],"show":[93,115],"can":[98,144],"be":[99,145],"approximated":[100],"using":[101],"local":[103],"central":[104],"limit":[105],"theorem":[106],"provable":[108],"accuracy":[109],"efficiency.":[112],"then":[114],"under":[117],"well-posedness":[119],"condition":[120],"model,":[123],"maximum":[125,134],"approximating":[128],"close":[131],"true":[137],"likelihood,":[139],"so":[140],"maximization":[143],"approximately":[146],"performed":[147],"by":[148],"maximizing":[149],"Gaussian":[151],"approximation":[152],"likelihood.":[156]},"counts_by_year":[],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}