{"id":"https://openalex.org/W4408520358","doi":"https://doi.org/10.1109/tnse.2025.3551767","title":"TVEG: Model Selection of the Time-Varying Exponential Family Distributions Graphical Models","display_name":"TVEG: Model Selection of the Time-Varying Exponential Family Distributions Graphical Models","publication_year":2025,"publication_date":"2025-03-17","ids":{"openalex":"https://openalex.org/W4408520358","doi":"https://doi.org/10.1109/tnse.2025.3551767"},"language":"en","primary_location":{"id":"doi:10.1109/tnse.2025.3551767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2025.3551767","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Network Science and Engineering","raw_type":"journal-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/A5100446289","display_name":"Juan Liu","orcid":"https://orcid.org/0000-0001-9118-3751"},"institutions":[{"id":"https://openalex.org/I31683504","display_name":"Beijing Forestry University","ror":"https://ror.org/04xv2pc41","country_code":"CN","type":"education","lineage":["https://openalex.org/I1327237609","https://openalex.org/I31683504","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Liu","raw_affiliation_strings":["School of Technology, Beijing Forestry University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9118-3751","affiliations":[{"raw_affiliation_string":"School of Technology, Beijing Forestry University, Beijing, China","institution_ids":["https://openalex.org/I31683504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014616639","display_name":"Guofeng Mei","orcid":"https://orcid.org/0000-0002-0494-5031"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Guofeng Mei","raw_affiliation_strings":["Technologies of Vision (TeV), Fondazione Bruno Kessler, Trento, Italy","Technologies of Vision (TeV), Fondazione Bruno Kessler, Italy"],"raw_orcid":"https://orcid.org/0000-0002-0494-5031","affiliations":[{"raw_affiliation_string":"Technologies of Vision (TeV), Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]},{"raw_affiliation_string":"Technologies of Vision (TeV), Fondazione Bruno Kessler, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064231378","display_name":"Yuanqing Xia","orcid":"https://orcid.org/0000-0002-5977-4911"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanqing Xia","raw_affiliation_strings":["Zhongyuan University of Technology, Henan, China"],"raw_orcid":"https://orcid.org/0000-0002-5977-4911","affiliations":[{"raw_affiliation_string":"Zhongyuan University of Technology, Henan, China","institution_ids":["https://openalex.org/I132586189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001956640","display_name":"Xiaoqun Wu","orcid":"https://orcid.org/0000-0001-5065-6460"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqun Wu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","School of Mathematics and Statistics, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5065-6460","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"School of Mathematics and Statistics, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027725400","display_name":"Jinhu L\u00fc","orcid":"https://orcid.org/0000-0003-0275-8387"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhu L\u00fc","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0275-8387","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04388819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"4","first_page":"2666","last_page":"2678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14509","display_name":"demographic modeling and climate adaptation","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T14509","display_name":"demographic modeling and climate adaptation","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exponential-family","display_name":"Exponential family","score":0.6096553206443787},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5955207943916321},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.539131760597229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4866279065608978},{"id":"https://openalex.org/keywords/natural-exponential-family","display_name":"Natural exponential family","score":0.46997755765914917},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4685783088207245},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4492345452308655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44167420268058777},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.4288298785686493},{"id":"https://openalex.org/keywords/exponential-distribution","display_name":"Exponential distribution","score":0.4262082576751709},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36866092681884766},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.33134472370147705},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.321763813495636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17073336243629456},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.14401865005493164},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.13974392414093018}],"concepts":[{"id":"https://openalex.org/C55974624","wikidata":"https://www.wikidata.org/wiki/Q1188504","display_name":"Exponential family","level":2,"score":0.6096553206443787},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5955207943916321},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.539131760597229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4866279065608978},{"id":"https://openalex.org/C60775368","wikidata":"https://www.wikidata.org/wiki/Q17099337","display_name":"Natural exponential family","level":3,"score":0.46997755765914917},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4685783088207245},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4492345452308655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44167420268058777},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.4288298785686493},{"id":"https://openalex.org/C55350006","wikidata":"https://www.wikidata.org/wiki/Q237193","display_name":"Exponential distribution","level":2,"score":0.4262082576751709},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36866092681884766},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.33134472370147705},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.321763813495636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17073336243629456},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.14401865005493164},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.13974392414093018}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tnse.2025.3551767","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnse.2025.3551767","pdf_url":null,"source":{"id":"https://openalex.org/S2484352698","display_name":"IEEE Transactions on Network Science and Engineering","issn_l":"2327-4697","issn":["2327-4697","2334-329X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Network Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2415565141","display_name":null,"funder_award_id":"61973241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3523307272","display_name":null,"funder_award_id":"61621003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4682412164","display_name":null,"funder_award_id":"BLX202338","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G6730084787","display_name":null,"funder_award_id":"62303052","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7007940310","display_name":null,"funder_award_id":"61836001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1549171236","https://openalex.org/W1970208077","https://openalex.org/W1991274888","https://openalex.org/W2009058783","https://openalex.org/W2021556180","https://openalex.org/W2025678883","https://openalex.org/W2026614436","https://openalex.org/W2065301447","https://openalex.org/W2068674173","https://openalex.org/W2093291778","https://openalex.org/W2105693192","https://openalex.org/W2106746326","https://openalex.org/W2138019504","https://openalex.org/W2524842917","https://openalex.org/W2587812844","https://openalex.org/W2592570417","https://openalex.org/W2593294478","https://openalex.org/W2774820752","https://openalex.org/W2791154213","https://openalex.org/W2801655981","https://openalex.org/W2899702797","https://openalex.org/W2962853966","https://openalex.org/W2963421812","https://openalex.org/W3005169540","https://openalex.org/W3010685466","https://openalex.org/W3011909246","https://openalex.org/W3022322085","https://openalex.org/W3031938913","https://openalex.org/W3035020452","https://openalex.org/W3043175749","https://openalex.org/W3044143895","https://openalex.org/W3111576330","https://openalex.org/W3156480000","https://openalex.org/W3178131779","https://openalex.org/W4213251304","https://openalex.org/W4250589301","https://openalex.org/W4292363360","https://openalex.org/W6638588478","https://openalex.org/W6677907686","https://openalex.org/W6677957080","https://openalex.org/W6678231584","https://openalex.org/W6679222004","https://openalex.org/W6680670352","https://openalex.org/W6689490952","https://openalex.org/W6697084107"],"related_works":["https://openalex.org/W198350940","https://openalex.org/W4235791879","https://openalex.org/W2130561717","https://openalex.org/W2732416952","https://openalex.org/W2619715168","https://openalex.org/W2962823242","https://openalex.org/W4253492336","https://openalex.org/W2903098718","https://openalex.org/W4226134799","https://openalex.org/W2734666369"],"abstract_inverted_index":{"The":[0,155],"undirected":[1],"graphical":[2,33,102],"model,":[3,9],"a":[4,11,20,27,31,135],"popular":[5],"class":[6],"of":[7,22,39,46,77,111,164,167,186],"statistical":[8],"offers":[10],"way":[12],"to":[13,29,35,85,107,122,139],"describe":[14],"and":[15,66,81,87,127,148,169,178,184],"explain":[16,36],"the":[17,37,44,55,75,97,109,120,124,141,153,160,170,174,182],"relationships":[18,38,45],"among":[19],"set":[21],"variables.":[23],"However,":[24],"it":[25],"remains":[26],"challenge":[28],"choose":[30],"certain":[32],"model":[34,177,180],"variables":[40,47],"adequately,":[41],"especially":[42],"when":[43],"are":[48],"rewiring":[49],"over":[50],"time.":[51],"This":[52],"paper":[53],"proposes":[54],"Time-Varying":[56],"Exponential":[57],"Family":[58],"Distributions":[59],"Graphical":[60],"(TVEG)":[61],"models,":[62],"with":[63,130],"time-varying":[64,86,144,175],"structures":[65],"exponential":[67,88,100,176],"family":[68,89,101],"node-wise":[69],"conditional":[70],"distributions.":[71],"TVEG":[72,112,187],"models":[73,80],"extend":[74],"scope":[76],"available":[78],"graph":[79],"can":[82],"be":[83],"applied":[84],"distribution":[90],"observation":[91],"data":[92,166],"in":[93],"reality.":[94],"We":[95,115,133],"propose":[96],"Temporally":[98],"Smoothed$L_{1}$-regularized":[99],"estimator":[103,106],"(TSLEG),":[104],"an":[105],"infer":[108],"structure":[110],"from":[113],"observations.":[114],"derive":[116,134],"sufficient":[117],"conditions":[118],"for":[119,143],"TSLEG":[121,142],"recover":[123],"block":[125],"partition":[126],"sparse":[128],"pattern":[129],"high":[131],"probability.":[132],"message-passing":[136],"optimization":[137],"method":[138],"solve":[140],"Ising,":[145],"Gaussian,":[146],"exponential,":[147],"Poisson":[149,179],"graphs":[150],"based":[151],"on":[152],"ADMM.":[154],"synthetic":[156],"network":[157],"simulations":[158],"corroborate":[159],"theoretical":[161],"analysis.":[162],"Analysing":[163],"real":[165],"stocks":[168],"US":[171],"Senate":[172],"by":[173],"indicates":[181],"effectiveness":[183],"practicality":[185],"models.":[188]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
