{"id":"https://openalex.org/W4411908864","doi":"https://doi.org/10.3389/fams.2025.1629658","title":"Corrigendum: Expectation-maximization alternating least squares for tensor network logistic regression","display_name":"Corrigendum: Expectation-maximization alternating least squares for tensor network logistic regression","publication_year":2025,"publication_date":"2025-07-01","ids":{"openalex":"https://openalex.org/W4411908864","doi":"https://doi.org/10.3389/fams.2025.1629658"},"language":"en","primary_location":{"id":"doi:10.3389/fams.2025.1629658","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fams.2025.1629658","pdf_url":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1629658/pdf","source":{"id":"https://openalex.org/S2597085352","display_name":"Frontiers in Applied Mathematics and Statistics","issn_l":"2297-4687","issn":["2297-4687"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Applied Mathematics and Statistics","raw_type":"journal-article"},"type":"erratum","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1629658/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016913204","display_name":"N Yamauchi","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoya Yamauchi","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031879419","display_name":"Hidekata Hontani","orcid":"https://orcid.org/0000-0001-9081-7740"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hidekata Hontani","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086158953","display_name":"Tatsuya Yokota","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Tatsuya Yokota","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan","RIKEN Center for Advanced Intelligence Project, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Aichi, Japan","institution_ids":["https://openalex.org/I197274945"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5086158953"],"corresponding_institution_ids":["https://openalex.org/I197274945","https://openalex.org/I4210126580"],"apc_list":{"value":1285,"currency":"USD","value_usd":1285},"apc_paid":{"value":1285,"currency":"USD","value_usd":1285},"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9690999984741211,"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/logistic-regression","display_name":"Logistic regression","score":0.8008350133895874},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4884127974510193},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.48198527097702026},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46936896443367004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46197760105133057},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.45303404331207275},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4461131691932678},{"id":"https://openalex.org/keywords/logistic-model-tree","display_name":"Logistic model tree","score":0.4383878707885742},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4370884597301483},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3336821496486664},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32916614413261414},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.19483280181884766},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.06418102979660034}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.8008350133895874},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4884127974510193},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.48198527097702026},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46936896443367004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46197760105133057},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.45303404331207275},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4461131691932678},{"id":"https://openalex.org/C61722155","wikidata":"https://www.wikidata.org/wiki/Q6667643","display_name":"Logistic model tree","level":3,"score":0.4383878707885742},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4370884597301483},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3336821496486664},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32916614413261414},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.19483280181884766},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.06418102979660034},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3389/fams.2025.1629658","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fams.2025.1629658","pdf_url":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1629658/pdf","source":{"id":"https://openalex.org/S2597085352","display_name":"Frontiers in Applied Mathematics and Statistics","issn_l":"2297-4687","issn":["2297-4687"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Applied Mathematics and Statistics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5ed7c01bad904e22b63fe16d4a010c5d","is_oa":true,"landing_page_url":"https://doaj.org/article/5ed7c01bad904e22b63fe16d4a010c5d","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Applied Mathematics and Statistics, Vol 11 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fams.2025.1629658","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fams.2025.1629658","pdf_url":"https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2025.1629658/pdf","source":{"id":"https://openalex.org/S2597085352","display_name":"Frontiers in Applied Mathematics and Statistics","issn_l":"2297-4687","issn":["2297-4687"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Applied Mathematics and Statistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411908864.pdf","grobid_xml":"https://content.openalex.org/works/W4411908864.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2947806671","https://openalex.org/W2390878257","https://openalex.org/W2338994166","https://openalex.org/W2144260821","https://openalex.org/W2141163797","https://openalex.org/W2118922860","https://openalex.org/W4313429348","https://openalex.org/W3136487442","https://openalex.org/W3048313722","https://openalex.org/W2533120240"],"abstract_inverted_index":{"4":[0],"There":[1],"were":[2,77,82],"errors":[3,293],"in":[4,7,18,74,85,137,308,333],"the":[5,8,14,28,37,51,63,75,87,92,102,107,110,113,301,305,320,342,460],"formula":[6],"paper.":[9],"We":[10,59],"had":[11,26,43],"originally":[12],"derived":[13,332],"correct":[15],"equations":[16],"(shown":[17],"5":[19],"Section":[20,138],"of":[21,23,101,109,304,322],"Derivation":[22],"Corrections)":[24],"and":[25,41,72,79,135,294],"implemented":[27,84],"computer":[29,88],"program":[30],"correctly.":[31],"However,":[32],"6":[33],"mistakes":[34],"occurred":[35],"during":[36],"paper":[38,76],"writing":[39],"stage,":[40],"we":[42,317,389],"not":[44,98,299],"noticed":[45],"it":[46],"until":[47],"now.We":[48],"report":[49],"that":[50,61,80,296,600],"error":[52],"was":[53,117],"caused":[54],"by":[55,614],"a":[56,334],"simple":[57],"typo.":[58],"confirmed":[60],"only":[62,318],"mathematical":[64],"formulas":[65,121],"8":[66],"(58),":[67],"(":[68,70,129,131,133,324,339],"59),":[69,132],"73)":[71,134],"(74)":[73,136,220],"incorrect,":[78],"they":[81],"correctly":[83],"9":[86],"programs":[89],"used":[90],"for":[91,291],"experiments.":[93],"Therefore,":[94],"this":[95],"revision":[96],"does":[97],"change":[99,300],"any":[100,309],"10":[103],"experimental":[104],"results":[105],"or":[106],"conclusions":[108,303],"original":[111,312],"paper.In":[112],"published":[114],"article,":[115],"there":[116],"an":[118],"error.":[119],"Some":[120],"have":[122,124],"typos.Corrections":[123],"been":[125,315],"made":[126],"to":[127],"Equations":[128],"58),":[130],"4.":[139],"These":[140],"previously":[141],"stated:14":[142],"\u03b2m":[143,183,221,254,619,628],"=":[144,163,184,203,222,237,255,273,353,393,412,430,447,501,522,538,553,573,605,620,633],"(Z":[145,164,185,204,223,238,256,274,527,543,554,565],"\u22a4":[146,155,165,175,186,195,205,215,224,233,239,249,257,266,275,285,376,424,441,457,489,562,575,578,587,590,595,622,630],"m":[147,151,156,162,166,170,176,187,191,196,202,206,210,216,225,229,234,236,240,244,250,258,262,267,272,276,280,286,348,378,446,491,516,518,528,530,544,546,555,557,566,568,576,579,583,585,588,591,617,623,627,631],"\u2126":[148,167,188,207,226,241,259,277,391,563,580,596,606,624],"t":[149,160,168,180,189,200,208,227,242,260,278,357,361,366,384,392,411,470,474,479,497,505,509,514,526,534,542,549,560,564,571,581,598,604,608,625],"Z":[150,154,169,174,190,194,209,214,228,232,243,248,261,265,279,284,515,577,582,589,626],")":[152,192,230,263,352,362,375,379,404,456,475,488,492,510],"-1":[153,173,193,213,231,247,264,283,548,559,570,597,607],"(\u03ba":[157,177,197,217,358,471,506],"\u2298":[158,178,198,218,359,472,507,532,602],"\u03c9":[159,179,199,360,410,473,508,533,603],"),(58)\u03b2(\u03f5)":[161],"+":[171,211,245,281,380,493,593],"\u03f5I)":[172,212,246,282],"),":[181],"(59)":[182,252],"),(73)\u03b2(\u03f5)":[201],"\u03c9).":[219],"\u03ba,(58)\u03b2(\u03f5)":[235],"\u03ba,":[251,268],"20":[253],"(73)":[269],"21":[270],"\u03b2(\u03f5)":[271],"\u03ba.":[287,609],"(74)The":[288],"authors":[289],"apologize":[290],"these":[292,297],"state":[295],"do":[298],"scientific":[302],"22":[306],"article":[307,313],"way.":[310],"The":[311,326],"has":[314],"updated.Here":[316],"show":[319],"derivation":[321],"equation":[323,338],"58).":[325],"remaining":[327],"three":[328],"corrections":[329],"can":[330],"be":[331],"25":[335],"similar":[336],"manner.First,":[337],"58)":[340],"is":[341,463,612],"weighted":[343],"least":[344],"squares":[345],"solution":[346],"forg(A":[347],",":[349,397,400,409,416,419,428,433,436,458],"v|\u03b8":[350],"(t)":[351,395,414],"\u2225\u2126":[354,467,502,523,539],"1":[355,364,382,396,415,432,468,477,495,503,512,524,540],"2":[356,365,383,386,387,399,418,435,469,478,496,499,500,504,513,520,521,525,536,537,541,551,552],"-\u2126":[363,476,511,547,558,569],"(L":[367,480],"(m)":[368,371,374,449,452,455,481,484,487],"\u2299":[369,372,450,453,482,485],"\u03a6":[370,451,483],"R":[373,406,426,443,454,486],"vec(A":[377,490],"v\u2126":[381,494],"1\u2225":[385,498],",(57)where":[388],"put":[390],"diag(\u03c9":[394],"\u03c9(t)":[398,402,417,421],"...,":[401,420,437],"N":[403,407,422,427,439,444],"\u2208":[405,425,442],"\u00d7N":[408],"[\u03c9":[413],"]":[423,440],"\u03ba":[429,434,438,592,594,601,632],"[\u03ba":[431],",Z":[445],"[(L":[448],"1],":[459],"cost":[461],"function":[462],"rewritten":[464],"as":[465],"30":[466],"\u03b2":[517,529,545,556,567,574,584],"\u2225":[519],"-\u03ba":[531],")\u2225":[535],"\u03ba)\u2225":[550],"\u03ba)":[561,572],"-2\u03b2":[586],"\u03ba.Note":[599],"Optimality":[610],"condition":[611],"given":[613],"\u2202g":[615],"\u2202\u03b2":[616],"\u03b2m=":[618],"2Z":[621],"-2Z":[629],"0.(1)":[634]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}