{"id":"https://openalex.org/W3196872837","doi":"https://doi.org/10.1109/isit45174.2021.9517717","title":"Estimating Properties of Dynamic Graphical Models","display_name":"Estimating Properties of Dynamic Graphical Models","publication_year":2021,"publication_date":"2021-07-12","ids":{"openalex":"https://openalex.org/W3196872837","doi":"https://doi.org/10.1109/isit45174.2021.9517717","mag":"3196872837"},"language":"en","primary_location":{"id":"doi:10.1109/isit45174.2021.9517717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5070167898","display_name":"Changlong Wu","orcid":"https://orcid.org/0000-0001-5255-1275"},"institutions":[{"id":"https://openalex.org/I117965899","display_name":"University of Hawai\u02bbi at M\u0101noa","ror":"https://ror.org/01wspgy28","country_code":"US","type":"education","lineage":["https://openalex.org/I117965899"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Changlong Wu","raw_affiliation_strings":["University of Hawaii,Manoa","University of Hawaii, Manoa"],"affiliations":[{"raw_affiliation_string":"University of Hawaii,Manoa","institution_ids":["https://openalex.org/I117965899"]},{"raw_affiliation_string":"University of Hawaii, Manoa","institution_ids":["https://openalex.org/I117965899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030506196","display_name":"Narayana Santhanam","orcid":"https://orcid.org/0000-0001-6515-6311"},"institutions":[{"id":"https://openalex.org/I117965899","display_name":"University of Hawai\u02bbi at M\u0101noa","ror":"https://ror.org/01wspgy28","country_code":"US","type":"education","lineage":["https://openalex.org/I117965899"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Narayana Santhanam","raw_affiliation_strings":["University of Hawaii,Manoa","University of Hawaii, Manoa"],"affiliations":[{"raw_affiliation_string":"University of Hawaii,Manoa","institution_ids":["https://openalex.org/I117965899"]},{"raw_affiliation_string":"University of Hawaii, Manoa","institution_ids":["https://openalex.org/I117965899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5070167898"],"corresponding_institution_ids":["https://openalex.org/I117965899"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1229809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"391","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9973000288009644,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9973000288009644,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9843999743461609,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9811000227928162,"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/graphical-model","display_name":"Graphical model","score":0.6263868808746338},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.6084511280059814},{"id":"https://openalex.org/keywords/bernoullis-principle","display_name":"Bernoulli's principle","score":0.5836437344551086},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4987640380859375},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.474413126707077},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4552832841873169},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4546138048171997},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.4474326968193054},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4284311830997467},{"id":"https://openalex.org/keywords/exponential-family","display_name":"Exponential family","score":0.4159194827079773},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.34155333042144775},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3207847476005554},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1516798436641693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09208279848098755}],"concepts":[{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.6263868808746338},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.6084511280059814},{"id":"https://openalex.org/C152361515","wikidata":"https://www.wikidata.org/wiki/Q181328","display_name":"Bernoulli's principle","level":2,"score":0.5836437344551086},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4987640380859375},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.474413126707077},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4552832841873169},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4546138048171997},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.4474326968193054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4284311830997467},{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.4159194827079773},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.34155333042144775},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3207847476005554},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1516798436641693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09208279848098755},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace 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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit45174.2021.9517717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit45174.2021.9517717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1642559065","display_name":null,"funder_award_id":"CCF-1619452","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3549316887","display_name":null,"funder_award_id":"CCF-0939370","funder_id":"https://openalex.org/F4320332170","funder_display_name":"Directorate for Engineering"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332170","display_name":"Directorate for Engineering","ror":"https://ror.org/00b6sbb32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W1735349781","https://openalex.org/W1972127338","https://openalex.org/W2073021346","https://openalex.org/W2108829665","https://openalex.org/W2326532020","https://openalex.org/W2482032619","https://openalex.org/W2950472458","https://openalex.org/W2958122143","https://openalex.org/W2970799136","https://openalex.org/W3172735654","https://openalex.org/W4236362309","https://openalex.org/W6767912158","https://openalex.org/W6787462274"],"related_works":["https://openalex.org/W2109986081","https://openalex.org/W1619264321","https://openalex.org/W2952350108","https://openalex.org/W2130561717","https://openalex.org/W4375945953","https://openalex.org/W2952102737","https://openalex.org/W1549765610","https://openalex.org/W1849082027","https://openalex.org/W4300555310","https://openalex.org/W2950440501"],"abstract_inverted_index":{"We":[0,39,80],"study":[1,27],"the":[2,12,18,31,37,62,65,98,105,110,121],"problem":[3],"of":[4,7,16,20,64,100],"estimating":[5],"properties":[6,58],"dynamic":[8],"graphical":[9],"models":[10],"in":[11],"non-asymptotic":[13],"regime.":[14],"Instead":[15],"characterizing":[17],"behavior":[19],"estimation":[21,78],"rules":[22],"with":[23,59,84],"asymptotic":[24],"consistency,":[25],"we":[26,114,126],"sharp":[28],"bounds":[29,72],"on":[30,120],"sample":[32,68,132],"size":[33,63,133],"required":[34,135],"to":[35,108],"estimate":[36,55],"properties.":[38,140],"show":[40,128],"that":[41,129],"for":[42,76,136],"certain":[43,56],"spatio-temporal":[44],"Markov":[45],"random":[46],"fields":[47],"governed":[48],"by":[49],"an":[50,101,130],"underlying":[51,66,102],"graph,":[52,103],"one":[53,94],"can":[54],"natural":[57],"logarithmic":[60],"(w.r.t.":[61],"graph)":[67],"complexity.":[69],"Matching":[70],"lower":[71],"are":[73],"also":[74,127],"established":[75],"such":[77],"problems.":[79],"highlight":[81],"our":[82],"results":[83],"a":[85,90],"\u201cbit":[86],"river\u201d":[87],"abstraction,":[88],"where":[89],"Bernoulli":[91],"source":[92],"at":[93],"node":[95],"flows":[96],"along":[97],"edges":[99],"and":[104],"task":[106],"is":[107,134],"obtain":[109],"flow":[111],"trajectory.":[112],"If":[113],"do":[115],"not":[116],"have":[117],"any":[118],"restriction":[119],"model":[122],"class":[123],"under":[124],"consideration,":[125],"exponential":[131],"even":[137],"very":[138],"simple":[139]},"counts_by_year":[],"updated_date":"2026-03-14T06:41:57.775601","created_date":"2025-10-10T00:00:00"}
