{"id":"https://openalex.org/W2904701286","doi":"https://doi.org/10.1609/aaai.v33i01.33013910","title":"Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction","display_name":"Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2904701286","doi":"https://doi.org/10.1609/aaai.v33i01.33013910","mag":"2904701286"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33013910","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013910","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v33i01.33013910","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047435295","display_name":"Akira Imakura","orcid":"https://orcid.org/0000-0003-4994-2499"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Imakura","raw_affiliation_strings":["University of Tsukuba"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110586631","display_name":"Momo Matsuda","orcid":null},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Momo Matsuda","raw_affiliation_strings":["University of Tsukuba"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063256241","display_name":"Xiucai Ye","orcid":"https://orcid.org/0000-0002-5547-3919"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiucai Ye","raw_affiliation_strings":["University of Tsukuba"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038336830","display_name":"Tetsuya Sakurai","orcid":"https://orcid.org/0000-0002-5789-7547"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Sakurai","raw_affiliation_strings":["University of Tsukuba"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tsukuba","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"01","first_page":"3910","last_page":"3918"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9781000018119812,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.8030173778533936},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5542970299720764},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.5292643308639526},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5221940875053406},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.5117001533508301},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5037080645561218},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.48857221007347107},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4864928126335144},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.4704403281211853},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.43549519777297974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4239398241043091},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.41687965393066406},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41455739736557007},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4062303900718689},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3689282536506653},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3584613800048828},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2907436490058899},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.14478957653045654}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.8030173778533936},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5542970299720764},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.5292643308639526},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5221940875053406},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.5117001533508301},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5037080645561218},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.48857221007347107},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4864928126335144},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.4704403281211853},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.43549519777297974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4239398241043091},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41687965393066406},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41455739736557007},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4062303900718689},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3689282536506653},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3584613800048828},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2907436490058899},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.14478957653045654},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v33i01.33013910","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013910","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/4280","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/4280","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4280/4158","source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33013910","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013910","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2174740613","display_name":"Development of eigenvalue analysis methods using a quadrature-type eigensolver with nonlinear transformations","funder_award_id":"18H03250","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3775791748","display_name":"Development of error resilience technology for complex moment-based parallel eigensolvers","funder_award_id":"17K12690","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6200036667","display_name":"\u975e\u7dda\u5f62\u975e\u8ca0\u884c\u5217\u5206\u89e3\u3092\u7528\u3044\u305f\u30c7\u30a3\u30fc\u30d7\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u8a08\u7b97\u624b\u6cd5\u306e\u958b\u767a","funder_award_id":"JPMJPR16U6","funder_id":"https://openalex.org/F4320334789","funder_display_name":"Japan Science and Technology Agency"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320334789","display_name":"Japan Science and Technology Agency","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1480487340","https://openalex.org/W1506806321","https://openalex.org/W1516503742","https://openalex.org/W1592106811","https://openalex.org/W1598589780","https://openalex.org/W1755117326","https://openalex.org/W1969204685","https://openalex.org/W1985258161","https://openalex.org/W1986850771","https://openalex.org/W1998906317","https://openalex.org/W2001619934","https://openalex.org/W2011994564","https://openalex.org/W2031968565","https://openalex.org/W2062388999","https://openalex.org/W2083203373","https://openalex.org/W2103560185","https://openalex.org/W2109531142","https://openalex.org/W2135346934","https://openalex.org/W2140095548","https://openalex.org/W2152538969","https://openalex.org/W2154872931","https://openalex.org/W2217442075","https://openalex.org/W2493525444","https://openalex.org/W2556757679","https://openalex.org/W2557392929","https://openalex.org/W2564758025","https://openalex.org/W2740101263","https://openalex.org/W2758624806","https://openalex.org/W2791277681","https://openalex.org/W2964332084","https://openalex.org/W3014771378","https://openalex.org/W3141898517","https://openalex.org/W4238530616","https://openalex.org/W4240166560","https://openalex.org/W4244030505","https://openalex.org/W6650842192","https://openalex.org/W6682644385","https://openalex.org/W6741940680"],"related_works":["https://openalex.org/W3089110333","https://openalex.org/W1995622179","https://openalex.org/W3125756894","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"Dimensionality":[0],"reduction":[1,156],"methods":[2,49,108,157],"that":[3,145],"project":[4],"highdimensional":[5],"data":[6],"to":[7,28,55,63,74,109],"a":[8,33,52,64,84,101],"low-dimensional":[9,34,58],"space":[10],"by":[11],"matrix":[12,23,105],"trace":[13,24,106],"optimization":[14,25,107],"are":[15],"widely":[16],"used":[17],"for":[18,32,69,93,104,158],"clustering":[19],"and":[20,122,135],"classification.":[21,72],"The":[22],"problem":[26,31],"leads":[27],"an":[29,133],"eigenvalue":[30],"subspace":[35],"construction,":[36],"preserving":[37],"certain":[38],"properties":[39],"of":[40,46,66,78,138],"the":[41,47,57,76,79,97,116,127,139,146,153,159,163],"original":[42],"data.":[43],"However,":[44],"most":[45],"existing":[48,154],"use":[50],"only":[51],"few":[53],"eigenvectors":[54,92],"construct":[56],"space,":[59],"which":[60,114],"may":[61],"lead":[62],"loss":[65],"useful":[67],"information":[68,80],"achieving":[70],"successful":[71],"Herein,":[73],"overcome":[75],"deficiency":[77],"loss,":[81],"we":[82,130],"propose":[83,132],"novel":[85],"complex":[86],"moment-based":[87],"supervised":[88],"eigenmap":[89],"including":[90],"multiple":[91],"dimensionality":[94,155],"reduction.":[95],"Furthermore,":[96],"proposed":[98,140,147,164],"method":[99,148,165],"provides":[100],"general":[102],"formulation":[103],"incorporate":[110],"with":[111,152],"ridge":[112],"regression,":[113],"models":[115],"linear":[117],"dependency":[118],"between":[119],"covariate":[120],"variables":[121],"univariate":[123],"labels.":[124],"To":[125],"reduce":[126],"computational":[128],"complexity,":[129],"also":[131],"efficient":[134],"parallel":[136,168],"implementation":[137],"method.":[141],"Numerical":[142],"experiments":[143],"indicate":[144],"is":[149],"competitive":[150],"compared":[151],"recognition":[160],"performance.":[161],"Additionally,":[162],"exhibits":[166],"high":[167],"efficiency.":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
