{"id":"https://openalex.org/W4323521037","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051977","title":"Joint graph learning from Gaussian observations in the presence of hidden nodes","display_name":"Joint graph learning from Gaussian observations in the presence of hidden nodes","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4323521037","doi":"https://doi.org/10.1109/ieeeconf56349.2022.10051977"},"language":"en","primary_location":{"id":"doi:10.1109/ieeeconf56349.2022.10051977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf56349.2022.10051977","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","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/A5001628625","display_name":"Samuel Rey","orcid":"https://orcid.org/0000-0003-1208-8997"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Samuel Rey","raw_affiliation_strings":["King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081211458","display_name":"Madeline Navarro","orcid":"https://orcid.org/0000-0002-3749-8856"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Madeline Navarro","raw_affiliation_strings":["Rice University,Dept. of ECE,Houston,USA","Dept. of ECE, Rice University, Houston, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rice University,Dept. of ECE,Houston,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Dept. of ECE, Rice University, Houston, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077810557","display_name":"Andrei Buciulea","orcid":"https://orcid.org/0000-0002-7256-920X"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Andrei Buciulea","raw_affiliation_strings":["King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012007074","display_name":"Santiago Segarra","orcid":"https://orcid.org/0000-0002-8408-9633"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago Segarra","raw_affiliation_strings":["Rice University,Dept. of ECE,Houston,USA","Dept. of ECE, Rice University, Houston, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rice University,Dept. of ECE,Houston,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Dept. of ECE, Rice University, Houston, USA","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054312245","display_name":"Antonio G. Marqu\u00e9s","orcid":"https://orcid.org/0000-0002-4642-7718"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio G. Marques","raw_affiliation_strings":["King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King Juan Carlos University,Dept. of Signal Theory and Comms.,Madrid,Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"Dept. of Signal Theory and Comms., King Juan Carlos University, Madrid, Kingdom of Spain","institution_ids":["https://openalex.org/I182083151"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5249,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.71858832,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"53","last_page":"57"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9941999912261963,"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":0.9941999912261963,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9940999746322632,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.986299991607666,"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/computer-science","display_name":"Computer science","score":0.6460684537887573},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5974289774894714},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5589649081230164},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.5521537065505981},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5076850652694702},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.5068719983100891},{"id":"https://openalex.org/keywords/hidden-variable-theory","display_name":"Hidden variable theory","score":0.4684465229511261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44911232590675354},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4469772279262543},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.43993791937828064},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40850141644477844},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33083170652389526}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6460684537887573},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5974289774894714},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5589649081230164},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.5521537065505981},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5076850652694702},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.5068719983100891},{"id":"https://openalex.org/C137002209","wikidata":"https://www.wikidata.org/wiki/Q898521","display_name":"Hidden variable theory","level":3,"score":0.4684465229511261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44911232590675354},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4469772279262543},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.43993791937828064},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40850141644477844},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33083170652389526},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf56349.2022.10051977","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf56349.2022.10051977","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 56th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1984197633","https://openalex.org/W1991252559","https://openalex.org/W2010192956","https://openalex.org/W2010824638","https://openalex.org/W2055234679","https://openalex.org/W2097581234","https://openalex.org/W2101491865","https://openalex.org/W2112090702","https://openalex.org/W2132555912","https://openalex.org/W2165009258","https://openalex.org/W2486096428","https://openalex.org/W2615556757","https://openalex.org/W2763292376","https://openalex.org/W2796431263","https://openalex.org/W2806008205","https://openalex.org/W2953689307","https://openalex.org/W2959406683","https://openalex.org/W2962759781","https://openalex.org/W2964012239","https://openalex.org/W2975682369","https://openalex.org/W2994097903","https://openalex.org/W3012969880","https://openalex.org/W3084183742","https://openalex.org/W3093204380","https://openalex.org/W3157999218","https://openalex.org/W3189983173","https://openalex.org/W3202127133","https://openalex.org/W3208382082","https://openalex.org/W3212653422","https://openalex.org/W4312076730","https://openalex.org/W4385732031","https://openalex.org/W4388323202","https://openalex.org/W6674754732","https://openalex.org/W6689213722","https://openalex.org/W6763961103","https://openalex.org/W6767939839","https://openalex.org/W6784173877","https://openalex.org/W6839580900"],"related_works":["https://openalex.org/W2776613281","https://openalex.org/W2106257677","https://openalex.org/W2964321162","https://openalex.org/W1877846107","https://openalex.org/W2070797946","https://openalex.org/W4322716735","https://openalex.org/W2185166290","https://openalex.org/W2962775488","https://openalex.org/W2952102737","https://openalex.org/W1549765610"],"abstract_inverted_index":{"Graph":[0],"learning":[1,9,59,153],"problems":[2],"are":[3,21,110],"typically":[4],"approached":[5],"by":[6,52,93,155],"focusing":[7],"on":[8],"the":[10,36,47,65,72,75,79,95,98,107,125,135,139,150,165],"topology":[11],"of":[12,42,67,74,97],"a":[13,40,56,113,144,157],"single":[14],"graph":[15,58,126,152],"when":[16],"signals":[17,109],"from":[18,112,138],"all":[19],"nodes":[20,43,77],"available.":[22],"However,":[23],"many":[24],"contemporary":[25],"setups":[26],"involve":[27],"multiple":[28],"related":[29],"networks":[30],"and,":[31],"moreover,":[32],"it":[33],"is":[34,44],"often":[35],"case":[37],"that":[38,61,102,106,148],"only":[39],"subset":[41],"observed":[45,108],"while":[46],"rest":[48],"remain":[49],"hidden.":[50],"Motivated":[51],"this,":[53],"we":[54,88,104,122,133,163],"propose":[55,143],"joint":[57,151],"method":[60],"takes":[62],"into":[63],"account":[64],"presence":[66,73],"hidden":[68,76,129],"(latent)":[69,130],"variables.":[70],"Intuitively,":[71],"renders":[78],"inference":[80],"task":[81,154],"ill-posed":[82],"and":[83,121,171,177],"challenging":[84],"to":[85,142],"solve,":[86],"so":[87],"overcome":[89],"this":[90],"detrimental":[91],"influence":[92],"harnessing":[94],"similarity":[96,127],"estimated":[99],"graphs.":[100,179],"To":[101],"end,":[103],"assume":[105],"drawn":[111],"Gaussian":[114],"Markov":[115],"random":[116],"field":[117],"with":[118,168],"latent":[119],"variables":[120],"carefully":[123],"model":[124],"among":[128],"nodes.":[131],"Then,":[132],"exploit":[134],"structure":[136],"resulting":[137],"previous":[140],"considerations":[141],"convex":[145],"optimization":[146],"problem":[147],"solves":[149],"providing":[156],"regularized":[158],"maximum":[159],"likelihood":[160],"estimator.":[161],"Finally,":[162],"compare":[164],"proposed":[166],"algorithm":[167],"different":[169],"baselines":[170],"evaluate":[172],"its":[173],"performance":[174],"over":[175],"synthetic":[176],"real-world":[178]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}