{"id":"https://openalex.org/W3204464503","doi":"https://doi.org/10.1080/10618600.2021.1984929","title":"Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model","display_name":"Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model","publication_year":2021,"publication_date":"2021-09-29","ids":{"openalex":"https://openalex.org/W3204464503","doi":"https://doi.org/10.1080/10618600.2021.1984929","mag":"3204464503"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2021.1984929","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2021.1984929","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2006.14217","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012834199","display_name":"Emanuele Aliverti","orcid":"https://orcid.org/0000-0002-6321-014X"},"institutions":[{"id":"https://openalex.org/I149461666","display_name":"Ca' Foscari University of Venice","ror":"https://ror.org/04yzxz566","country_code":"IT","type":"education","lineage":["https://openalex.org/I149461666"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Emanuele Aliverti","raw_affiliation_strings":["Department of Economics, Ca\u2019 Foscari University of Venice, Venezia, Italy;;"],"raw_orcid":"https://orcid.org/0000-0002-6321-014X","affiliations":[{"raw_affiliation_string":"Department of Economics, Ca\u2019 Foscari University of Venice, Venezia, Italy;;","institution_ids":["https://openalex.org/I149461666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085213521","display_name":"Massimiliano Russo","orcid":"https://orcid.org/0000-0003-4953-9341"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I4210117453","display_name":"Dana-Farber Cancer Institute","ror":"https://ror.org/02jzgtq86","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210117453"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Massimiliano Russo","raw_affiliation_strings":["Department of Data Science, Dana-Farber Cancer Institute, Boston, MA","Harvard\u2013MIT Center for Regulatory Science, Harvard Medical School, Boston, MA;;"],"raw_orcid":"https://orcid.org/0000-0003-4953-9341","affiliations":[{"raw_affiliation_string":"Department of Data Science, Dana-Farber Cancer Institute, Boston, MA","institution_ids":["https://openalex.org/I4210117453"]},{"raw_affiliation_string":"Harvard\u2013MIT Center for Regulatory Science, Harvard Medical School, Boston, MA;;","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012834199"],"corresponding_institution_ids":["https://openalex.org/I149461666"],"apc_list":null,"apc_paid":null,"fwci":0.6824,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.7575791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"31","issue":"2","first_page":"502","last_page":"511"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9984999895095825,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9984999895095825,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7053400278091431},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.6928532719612122},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5407971739768982},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37629181146621704},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3760608434677124},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.36194556951522827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3275721073150635},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27568143606185913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053400278091431},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6928532719612122},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5407971739768982},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37629181146621704},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3760608434677124},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.36194556951522827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3275721073150635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27568143606185913}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1080/10618600.2021.1984929","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2021.1984929","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2006.14217","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.14217","pdf_url":"https://arxiv.org/pdf/2006.14217","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:figshare.com:article/16699343","is_oa":true,"landing_page_url":"https://figshare.com/articles/dataset/Stratified_stochastic_variational_inference_for_high-dimensional_network_factor_model/16699343","pdf_url":null,"source":{"id":"https://openalex.org/S4306402621","display_name":"INDIGO (University of Illinois at Chicago)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39422238","host_organization_name":"University of Illinois Chicago","host_organization_lineage":["https://openalex.org/I39422238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Dataset"},{"id":"pmh:oai:iris.unive.it:10278/3743850","is_oa":true,"landing_page_url":"http://hdl.handle.net/10278/3743850","pdf_url":null,"source":{"id":"https://openalex.org/S4306402336","display_name":"ARCA (Universit\u00e0 Ca' Foscari Venezia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149461666","host_organization_name":"Ca' Foscari University of Venice","host_organization_lineage":["https://openalex.org/I149461666"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:www.research.unipd.it:11577/3470388","is_oa":true,"landing_page_url":"https://hdl.handle.net/11577/3470388","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"doi:10.6084/m9.figshare.16699343.v2","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.16699343.v2","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2006.14217","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2006.14217","pdf_url":"https://arxiv.org/pdf/2006.14217","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.6899999976158142}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321966","display_name":"Universit\u00e0 degli Studi di Padova","ror":"https://ror.org/00240q980"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W229097380","https://openalex.org/W597750194","https://openalex.org/W606561187","https://openalex.org/W634934296","https://openalex.org/W1848620603","https://openalex.org/W1992605514","https://openalex.org/W1994616650","https://openalex.org/W1999653836","https://openalex.org/W2010768245","https://openalex.org/W2020018100","https://openalex.org/W2023246751","https://openalex.org/W2041923730","https://openalex.org/W2061163551","https://openalex.org/W2066459332","https://openalex.org/W2073627497","https://openalex.org/W2083875149","https://openalex.org/W2087409009","https://openalex.org/W2097880196","https://openalex.org/W2099878672","https://openalex.org/W2108306139","https://openalex.org/W2123082179","https://openalex.org/W2166851633","https://openalex.org/W2225156818","https://openalex.org/W2416050356","https://openalex.org/W2559655401","https://openalex.org/W2594169039","https://openalex.org/W2754251575","https://openalex.org/W2789289055","https://openalex.org/W2936854052","https://openalex.org/W2963512140","https://openalex.org/W2979879093","https://openalex.org/W3037029101","https://openalex.org/W3099329193","https://openalex.org/W3100557905","https://openalex.org/W3101380508","https://openalex.org/W3101859177","https://openalex.org/W3102905194","https://openalex.org/W3104477937","https://openalex.org/W3117508693","https://openalex.org/W3160872503","https://openalex.org/W4212863985","https://openalex.org/W4235019172","https://openalex.org/W4235345084","https://openalex.org/W4294562888","https://openalex.org/W4302434451"],"related_works":["https://openalex.org/W2151689585","https://openalex.org/W2380816257","https://openalex.org/W3087071515","https://openalex.org/W4283726152","https://openalex.org/W1525770572","https://openalex.org/W1485888979","https://openalex.org/W3172507773","https://openalex.org/W2806680938","https://openalex.org/W4302285290","https://openalex.org/W2764679420"],"abstract_inverted_index":{"There":[0],"has":[1],"been":[2],"considerable":[3],"recent":[4],"interest":[5],"in":[6,46,102],"Bayesian":[7,77],"modeling":[8,66],"of":[9,19,67,85,106,116],"high-dimensional":[10,47],"networks":[11],"via":[12,79],"latent":[13,56,64],"space":[14,65],"approaches.":[15],"When":[16],"the":[17,55,88,117],"number":[18],"nodes":[20],"increases,":[21],"estimation":[22],"based":[23],"on":[24,40,54],"Markov":[25],"chain":[26],"Monte":[27],"Carlo":[28],"can":[29],"be":[30],"extremely":[31],"slow":[32],"and":[33,94,97],"show":[34,91],"poor":[35],"mixing,":[36],"thereby":[37],"motivating":[38],"research":[39],"alternative":[41],"algorithms":[42,73,90,119],"that":[43],"scale":[44],"well":[45],"settings.":[48],"In":[49],"this":[50],"article,":[51],"we":[52],"focus":[53],"factor":[57],"model,":[58],"a":[59],"widely":[60],"used":[61],"approach":[62],"for":[63],"network":[68,86],"data.":[69],"We":[70],"develop":[71],"scalable":[72],"to":[74,99],"conduct":[75,100],"approximate":[76],"inference":[78,101],"stochastic":[80],"optimization.":[81],"Leveraging":[82],"sparse":[83],"representations":[84],"data,":[87],"proposed":[89,118],"massive":[92],"computational":[93],"storage":[95],"benefits,":[96],"allow":[98],"settings":[103],"with":[104,111],"thousands":[105],"nodes.":[107],"An":[108],"R":[109],"package":[110],"an":[112],"efficient":[113],"c++":[114],"implementation":[115],"is":[120],"provided.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}