{"id":"https://openalex.org/W3108522782","doi":"https://doi.org/10.1109/tsp.2020.3039880","title":"Network Topology Inference From Heterogeneous Incomplete Graph Signals","display_name":"Network Topology Inference From Heterogeneous Incomplete Graph Signals","publication_year":2020,"publication_date":"2020-12-02","ids":{"openalex":"https://openalex.org/W3108522782","doi":"https://doi.org/10.1109/tsp.2020.3039880","mag":"3108522782"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2020.3039880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3039880","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","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/A5101695675","display_name":"Xiao Yang","orcid":"https://orcid.org/0000-0001-5527-1762"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Yang","raw_affiliation_strings":["State Key Laboratory of Integrated Service Networks, Institute of Information Science, Xidian University, Xi\u2019an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-5527-1762","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, Institute of Information Science, Xidian University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029337392","display_name":"Min Sheng","orcid":"https://orcid.org/0000-0002-7762-5063"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Sheng","raw_affiliation_strings":["State Key Laboratory of Integrated Service Networks, Institute of Information Science, Xidian University, Xi\u2019an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-7762-5063","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Networks, Institute of Information Science, Xidian University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101942697","display_name":"Yanli Yuan","orcid":"https://orcid.org/0000-0003-4592-5333"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yanli Yuan","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-4592-5333","affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore, Singapore","institution_ids":["https://openalex.org/I152815399"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030858163","display_name":"Tony Q. S. Quek","orcid":"https://orcid.org/0000-0002-4037-3149"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Tony Q.S. Quek","raw_affiliation_strings":["Singapore University of Technology and Design, Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-4037-3149","affiliations":[{"raw_affiliation_string":"Singapore University of Technology and Design, Singapore, Singapore","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.043,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.82677507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"69","issue":null,"first_page":"314","last_page":"327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.996999979019165,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.996999979019165,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9965000152587891,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.6919494271278381},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.6552300453186035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6161879897117615},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5797169208526611},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5740410685539246},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5153390765190125},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48178526759147644},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43125784397125244},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4207083582878113},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.41305768489837646},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.384808748960495},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3290524482727051},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2868283987045288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18258973956108093},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1761755347251892}],"concepts":[{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.6919494271278381},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.6552300453186035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6161879897117615},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5797169208526611},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5740410685539246},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5153390765190125},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48178526759147644},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43125784397125244},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4207083582878113},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.41305768489837646},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.384808748960495},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3290524482727051},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2868283987045288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18258973956108093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1761755347251892},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp.2020.3039880","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2020.3039880","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"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 Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G221963292","display_name":null,"funder_award_id":"U19B2025","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3283882023","display_name":null,"funder_award_id":"91638202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8114394444","display_name":null,"funder_award_id":"61725103","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W48439977","https://openalex.org/W1958662094","https://openalex.org/W1974105260","https://openalex.org/W1990488619","https://openalex.org/W2029460515","https://openalex.org/W2044758663","https://openalex.org/W2058616517","https://openalex.org/W2077870633","https://openalex.org/W2081746825","https://openalex.org/W2097581234","https://openalex.org/W2097596242","https://openalex.org/W2101491865","https://openalex.org/W2105591985","https://openalex.org/W2112681514","https://openalex.org/W2132555912","https://openalex.org/W2146332392","https://openalex.org/W2147609908","https://openalex.org/W2163707651","https://openalex.org/W2164278908","https://openalex.org/W2165009258","https://openalex.org/W2169038197","https://openalex.org/W2191264216","https://openalex.org/W2389980101","https://openalex.org/W2480680997","https://openalex.org/W2545344914","https://openalex.org/W2585019672","https://openalex.org/W2593294478","https://openalex.org/W2612195446","https://openalex.org/W2615556757","https://openalex.org/W2643391362","https://openalex.org/W2798585159","https://openalex.org/W2798729876","https://openalex.org/W2799178092","https://openalex.org/W2804375450","https://openalex.org/W2887005491","https://openalex.org/W2936036845","https://openalex.org/W2950190315","https://openalex.org/W2959406683","https://openalex.org/W2963384510","https://openalex.org/W2963489521","https://openalex.org/W2963702033","https://openalex.org/W2963818281","https://openalex.org/W2963893933","https://openalex.org/W2964012239","https://openalex.org/W2994097903","https://openalex.org/W2999687012","https://openalex.org/W3004555699","https://openalex.org/W3012969880","https://openalex.org/W3100282875","https://openalex.org/W3103870504","https://openalex.org/W4285719527","https://openalex.org/W4292363360","https://openalex.org/W6641158408","https://openalex.org/W6677111876","https://openalex.org/W6682035934","https://openalex.org/W6684745505","https://openalex.org/W6689213722","https://openalex.org/W6704098073"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2776613281","https://openalex.org/W2070797946","https://openalex.org/W2122332063","https://openalex.org/W4200372685"],"abstract_inverted_index":{"Inferring":[0],"network":[1,20,25,79],"topologies":[2,80],"from":[3,70],"observed":[4],"graph-structured":[5],"data":[6,58,69,120],"(also":[7],"known":[8],"as":[9],"graph":[10,108,140,146,179,194,203],"signals)":[11],"is":[12,121,171,213],"a":[13,62,71,105],"crucial":[14],"task":[15],"in":[16,96,245],"many":[17,41],"applications":[18],"of":[19,73,98,107,118,132,164,177,188,220,242],"science.":[21],"Existing":[22],"papers":[23],"on":[24,66,127,192,200,229],"topology":[26,93,147],"inference":[27,94],"typically":[28],"assume":[29],"that":[30,64,103,150,208],"the":[31,56,85,92,100,115,128,156,162,175,178,186,193,201,210,217,221,236,240],"observations":[32,46],"at":[33],"all":[34],"nodes":[35],"are":[36,40,135],"available.":[37],"However,":[38],"there":[39],"situations":[42],"where":[43],"only":[44],"partial":[45],"can":[47,152],"be":[48],"collected":[49],"due":[50],"to":[51,76,137,160,184,215],"application-specific":[52],"constraints.":[53],"To":[54],"handle":[55],"missing":[57,165],"problem,":[59],"we":[60,151,225],"propose":[61],"framework":[63],"relies":[65],"heterogeneous":[67],"incomplete":[68,119],"collection":[72],"related":[74,158],"networks":[75,159],"identify":[77],"multiple":[78,157],"simultaneously.":[81],"This":[82],"work":[83],"advocates":[84],"Gaussian":[86],"graphical":[87],"model":[88],"(GGM)":[89],"and":[90,123,181,232,235],"casts":[91],"problem":[95],"terms":[97],"estimating":[99],"precision":[101],"matrix":[102,117],"has":[104],"form":[106],"Laplacian.":[109],"Firstly,":[110],"an":[111,205],"unbiased":[112],"estimator":[113,180],"for":[114],"covariance":[116],"established":[122],"then":[124],"algorithms":[125],"based":[126,199],"alternating":[129],"direction":[130],"method":[131,228,244],"multipliers":[133],"(ADMM)":[134],"developed":[136],"jointly":[138],"estimate":[139,144],"topologies,":[141],"rather":[142],"than":[143],"each":[145],"separately.":[148],"So":[149],"borrow":[153],"information":[154],"across":[155],"eliminate":[161],"impact":[163],"data.":[166],"Moreover,":[167],"non-asymptotic":[168],"statistical":[169],"analysis":[170],"provided,":[172],"which":[173],"proves":[174],"consistency":[176],"enables":[182],"us":[183],"investigate":[185],"effect":[187],"several":[189],"key":[190],"factors":[191],"estimation":[195,218],"error":[196],"bound.":[197],"Furthermore,":[198],"consistent":[202],"estimator,":[204],"adaptive":[206],"algorithm":[207],"utilizes":[209],"reweighting":[211],"scheme":[212],"proposed":[214],"improve":[216],"accuracy":[219],"graph-edge":[222],"structure.":[223],"Finally,":[224],"evaluate":[226],"our":[227,243],"both":[230],"real":[231],"synthetic":[233],"datasets,":[234],"experimental":[237],"results":[238],"demonstrate":[239],"advantage":[241],"comparison":[246],"with":[247],"benchmarking":[248],"algorithms.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}