{"id":"https://openalex.org/W7092515560","doi":"https://doi.org/10.1109/tsp.2025.3620539","title":"An Effective Iterative Solution for Independent Vector Analysis With Convergence Guarantees","display_name":"An Effective Iterative Solution for Independent Vector Analysis With Convergence Guarantees","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7092515560","doi":"https://doi.org/10.1109/tsp.2025.3620539"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2025.3620539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3620539","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":true,"oa_status":"green","oa_url":"https://hal.science/hal-04785828v2/file/main.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Cl\u00e9ment Cosserat","orcid":"https://orcid.org/0009-0008-2082-4812"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Cl\u00e9ment Cosserat","raw_affiliation_strings":["OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ben Gabrielson","orcid":"https://orcid.org/0000-0001-9217-6641"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ben Gabrielson","raw_affiliation_strings":["Department of CSEE, University of Maryland Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of CSEE, University of Maryland Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Emilie Chouzenoux","orcid":"https://orcid.org/0000-0003-3631-6093"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Emilie Chouzenoux","raw_affiliation_strings":["OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jean-Christophe Pesquet","orcid":"https://orcid.org/0000-0002-5943-8061"},"institutions":[{"id":"https://openalex.org/I277688954","display_name":"Universit\u00e9 Paris-Saclay","ror":"https://ror.org/03xjwb503","country_code":"FR","type":"education","lineage":["https://openalex.org/I277688954"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Christophe Pesquet","raw_affiliation_strings":["OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France"],"affiliations":[{"raw_affiliation_string":"OPIS, Inria Saclay, Universit\u00e9 Paris-Saclay, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I277688954"]}]},{"author_position":"last","author":{"id":null,"display_name":"T\u00fclay Adali","orcid":"https://orcid.org/0000-0003-0594-2796"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T\u00fclay Adali","raw_affiliation_strings":["Department of CSEE, University of Maryland Baltimore County (UMBC), Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of CSEE, University of Maryland Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I277688954"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56802424,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"73","issue":null,"first_page":"4718","last_page":"4733"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.000699999975040555,"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/convergence","display_name":"Convergence (economics)","score":0.6855000257492065},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5878999829292297},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.5759999752044678},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5209000110626221},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4925999939441681},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.4490000009536743},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4415999948978424},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.4083000123500824}],"concepts":[{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6855000257492065},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5878999829292297},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.5759999752044678},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.546500027179718},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5198000073432922},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5130000114440918},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4925999939441681},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4415999948978424},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44020000100135803},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.4083000123500824},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.38670000433921814},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.37770000100135803},{"id":"https://openalex.org/C89106044","wikidata":"https://www.wikidata.org/wiki/Q45284","display_name":"Likelihood function","level":3,"score":0.36160001158714294},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3433000147342682},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C138405894","wikidata":"https://www.wikidata.org/wiki/Q3179949","display_name":"Multivariate random variable","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2025.3620539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2025.3620539","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"},{"id":"pmh:oai:HAL:hal-04785828v2","is_oa":true,"landing_page_url":"https://hal.science/hal-04785828v2/file/main.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"IEEE Transactions on Signal Processing, 2025, 73, pp.4718 - 4733. ⟨10.1109/TSP.2025.3620539⟩","raw_type":"Journal articles"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04785828v2","is_oa":true,"landing_page_url":"https://hal.science/hal-04785828v2/file/main.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4406922466","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"IEEE Transactions on Signal Processing, 2025, 73, pp.4718 - 4733. ⟨10.1109/TSP.2025.3620539⟩","raw_type":"Journal articles"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G330832463","display_name":null,"funder_award_id":"NSF 2316420","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W205960364","https://openalex.org/W1539811621","https://openalex.org/W1543386260","https://openalex.org/W1845880232","https://openalex.org/W1946620893","https://openalex.org/W1986589478","https://openalex.org/W1991840148","https://openalex.org/W1996195522","https://openalex.org/W2015757061","https://openalex.org/W2027982384","https://openalex.org/W2035128299","https://openalex.org/W2040985763","https://openalex.org/W2055637322","https://openalex.org/W2072548008","https://openalex.org/W2072635184","https://openalex.org/W2084147096","https://openalex.org/W2094345233","https://openalex.org/W2096663965","https://openalex.org/W2099741732","https://openalex.org/W2113992915","https://openalex.org/W2129732816","https://openalex.org/W2162615138","https://openalex.org/W2164016507","https://openalex.org/W2170768669","https://openalex.org/W2259139337","https://openalex.org/W2539141352","https://openalex.org/W2900051367","https://openalex.org/W2903112826","https://openalex.org/W2913406796","https://openalex.org/W2937789396","https://openalex.org/W2940652807","https://openalex.org/W2993403400","https://openalex.org/W3015678657","https://openalex.org/W3021380660","https://openalex.org/W3030881924","https://openalex.org/W3080684048","https://openalex.org/W3118110915","https://openalex.org/W4394754904","https://openalex.org/W4400942727"],"related_works":[],"abstract_inverted_index":{"Independent":[0],"vector":[1],"analysis":[2],"(IVA)":[3],"is":[4],"an":[5],"attractive":[6],"solution":[7],"to":[8,93,109,133],"address":[9],"the":[10,20,40,49,57,63,70,74,77,86,89,95,99,103,118,139,143],"problem":[11],"of":[12,23,51,65,73,88,102,120,142,161],"joint":[13,71],"blind":[14],"source":[15,54,104],"separation":[16],"(JBSS),":[17],"that":[18,44,68,157],"is,":[19],"simultaneous":[21],"extraction":[22],"latent":[24],"sources":[25,78,153],"from":[26],"several":[27],"datasets":[28],"implicitly":[29],"sharing":[30],"some":[31],"information.":[32],"Among":[33],"IVA":[34],"approaches,":[35],"we":[36,84,146],"focus":[37],"here":[38],"on":[39,126],"celebrated":[41],"IVA-G":[42,59],"model,":[43],"describes":[45],"observed":[46],"data":[47,90],"through":[48],"mixing":[50],"independent":[52],"Gaussian":[53],"vectors":[55],"across":[56],"datasets.":[58],"algorithms":[60],"usually":[61],"seek":[62],"values":[64],"demixing":[66,81,96],"matrices":[67,97,101],"maximize":[69],"likelihood":[72,87],"datasets,":[75],"estimating":[76],"using":[79],"these":[80],"matrices.":[82],"Instead,":[83],"write":[85],"with":[91,130,154],"respect":[92],"both":[94],"and":[98],"precision":[100],"estimates.":[105],"This":[106],"allows":[107],"us":[108],"formulate":[110],"a":[111,121,134],"cost":[112],"function":[113],"whose":[114],"mathematical":[115],"properties":[116,141],"enable":[117],"use":[119],"proximal":[122],"alternating":[123],"algorithm":[124],"based":[125],"closed":[127],"form":[128],"operators":[129],"provable":[131],"convergence":[132,140],"critical":[135],"point.":[136],"After":[137],"establishing":[138],"new":[144],"algorithm,":[145],"illustrate":[147],"its":[148],"desirable":[149],"performance":[150],"in":[151],"separating":[152],"covariance":[155],"structures":[156],"represent":[158],"varying":[159],"degrees":[160],"difficulty":[162],"for":[163],"JBSS.":[164]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-21T00:00:00"}