{"id":"https://openalex.org/W2053222984","doi":"https://doi.org/10.1109/smc.2014.6974147","title":"A note on the correlated multiple matrix completion based on the convex optimization method","display_name":"A note on the correlated multiple matrix completion based on the convex optimization method","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2053222984","doi":"https://doi.org/10.1109/smc.2014.6974147","mag":"2053222984"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2014.6974147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2014.6974147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5004624497","display_name":"Shunsuke Horii","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]},{"id":"https://openalex.org/I4210143629","display_name":"World Education","ror":"https://ror.org/040k7ca93","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210143629"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Shunsuke Horii","raw_affiliation_strings":["Waseda University, Tokyo, Japan","Global Education Center"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Global Education Center","institution_ids":["https://openalex.org/I4210143629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110471799","display_name":"Toshiyasu Matsushima","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toshiyasu Matsushima","raw_affiliation_strings":["Waseda University, Tokyo, Japan","School of Fundamental Science and Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"School of Fundamental Science and Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025082609","display_name":"Shigeichi Hirasawa","orcid":"https://orcid.org/0009-0003-0924-1038"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shigeichi Hirasawa","raw_affiliation_strings":["Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.322,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.615625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"113","issue":null,"first_page":"1618","last_page":"1623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9915000200271606,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.8361691236495972},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.7843682765960693},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.670508623123169},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.6400560140609741},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5999940633773804},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5468752384185791},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5451239347457886},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5293078422546387},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4624156951904297},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4307129383087158},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4160684645175934},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.3628430962562561},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3515973687171936},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.2830576002597809},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.2599676251411438},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1027975082397461},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.10248041152954102}],"concepts":[{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.8361691236495972},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.7843682765960693},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.670508623123169},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.6400560140609741},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5999940633773804},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5468752384185791},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5451239347457886},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5293078422546387},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4624156951904297},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4307129383087158},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4160684645175934},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3628430962562561},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3515973687171936},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2830576002597809},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.2599676251411438},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1027975082397461},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.10248041152954102},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc.2014.6974147","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2014.6974147","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1976618413","https://openalex.org/W2045079045","https://openalex.org/W2057624533","https://openalex.org/W2102515753","https://openalex.org/W2103972604","https://openalex.org/W2117420919","https://openalex.org/W2164278908","https://openalex.org/W2611328865","https://openalex.org/W6684379799"],"related_works":["https://openalex.org/W3018593348","https://openalex.org/W2896364421","https://openalex.org/W2478976345","https://openalex.org/W4206056232","https://openalex.org/W3099505889","https://openalex.org/W2371241905","https://openalex.org/W2547188920","https://openalex.org/W3103289951","https://openalex.org/W2808486553","https://openalex.org/W3173811578"],"abstract_inverted_index":{"In":[0,42,133],"this":[1,134],"paper,":[2,135],"we":[3,45,51,136],"consider":[4,112],"a":[5,70,108],"completion":[6,13,57,80,141],"problem":[7,14,17,142,168],"of":[8,22,101,115,153,176,183],"multiple":[9,76,139],"related":[10,49],"matrices.":[11,77,157],"Matrix":[12],"is":[15,69,91,105],"the":[16,23,83,102,113,116,138,144,151,154,166,172,181],"to":[18,73],"estimate":[19],"unobserved":[20],"elements":[21],"matrix":[24,64,67,85,140],"from":[25],"observed":[26],"elements.":[27],"It":[28],"has":[29,58],"many":[30],"applications":[31],"such":[32],"as":[33,143],"collaborative":[34],"filtering,":[35],"computer":[36],"vision,":[37],"biology,":[38],"and":[39,120,193],"so":[40],"on.":[41],"cases":[43],"where":[44],"can":[46,52],"obtain":[47],"some":[48,88,127],"matrices,":[50],"expect":[53],"that":[54,92,106],"their":[55],"simultaneous":[56],"better":[59],"performance":[60,125],"than":[61],"completing":[62],"each":[63],"independently.":[65],"Collective":[66],"factorization":[68,86],"powerful":[71],"approach":[72,185],"jointly":[74],"factorize":[75],"However,":[78],"existing":[79,94,110],"algorithms":[81,95,111],"for":[82],"collective":[84],"have":[87],"drawbacks.":[89],"One":[90],"most":[93],"are":[96,129],"based":[97,170],"on":[98,171,189],"non-convex":[99],"formulations":[100],"problem.":[103,147],"Another":[104],"only":[107],"few":[109],"strength":[114,152],"relation":[117,155],"among":[118,156],"matrices":[119,128],"it":[121,149],"results":[122],"in":[123],"worse":[124],"when":[126],"actually":[130],"not":[131],"related.":[132],"formulate":[137],"convex":[145],"optimization":[146,162],"Moreover,":[148],"considers":[150],"We":[158,179],"also":[159],"develop":[160],"an":[161],"algorithm":[163],"which":[164],"solves":[165],"proposed":[167],"efficiently":[169],"alternating":[173],"direction":[174],"method":[175],"multipliers":[177],"(ADMM).":[178],"verify":[180],"effectiveness":[182],"our":[184],"through":[186],"numerical":[187],"experiments":[188],"both":[190],"synthetic":[191],"data":[192,195],"real":[194],"set:":[196],"MovieLens.":[197]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
