{"id":"https://openalex.org/W2982368516","doi":"https://doi.org/10.1109/bcd.2019.8885337","title":"Scalable Laplacian Regularized Least Squares Classification on Anchor Graph","display_name":"Scalable Laplacian Regularized Least Squares Classification on Anchor Graph","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2982368516","doi":"https://doi.org/10.1109/bcd.2019.8885337","mag":"2982368516"},"language":"en","primary_location":{"id":"doi:10.1109/bcd.2019.8885337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bcd.2019.8885337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD)","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/A5087977941","display_name":"Shozo Saeki","orcid":null},"institutions":[{"id":"https://openalex.org/I43545212","display_name":"Ehime University","ror":"https://ror.org/017hkng22","country_code":"JP","type":"education","lineage":["https://openalex.org/I43545212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shozo Saeki","raw_affiliation_strings":["Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan","institution_ids":["https://openalex.org/I43545212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083744980","display_name":"Minoru Kawahara","orcid":null},"institutions":[{"id":"https://openalex.org/I43545212","display_name":"Ehime University","ror":"https://ror.org/017hkng22","country_code":"JP","type":"education","lineage":["https://openalex.org/I43545212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Minoru Kawahara","raw_affiliation_strings":["Center for Information Technology, Ehime University, Matsuyama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Information Technology, Ehime University, Matsuyama, Japan","institution_ids":["https://openalex.org/I43545212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051406503","display_name":"Hirohisa Aman","orcid":"https://orcid.org/0000-0001-7074-5225"},"institutions":[{"id":"https://openalex.org/I43545212","display_name":"Ehime University","ror":"https://ror.org/017hkng22","country_code":"JP","type":"education","lineage":["https://openalex.org/I43545212"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hirohisa Aman","raw_affiliation_strings":["Center for Information Technology, Ehime University, Matsuyama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Information Technology, Ehime University, Matsuyama, Japan","institution_ids":["https://openalex.org/I43545212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1017,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45711496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"71","last_page":"76"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9977999925613403,"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/T10057","display_name":"Face and Expression Recognition","score":0.9958000183105469,"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/scalability","display_name":"Scalability","score":0.8190903663635254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6766321659088135},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6444882154464722},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5691547393798828},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5588118433952332},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37133145332336426},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34827709197998047},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33380937576293945}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8190903663635254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6766321659088135},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6444882154464722},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5691547393798828},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5588118433952332},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37133145332336426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34827709197998047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33380937576293945},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bcd.2019.8885337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bcd.2019.8885337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1480376833","https://openalex.org/W1574496672","https://openalex.org/W1664825283","https://openalex.org/W2076280956","https://openalex.org/W2086504823","https://openalex.org/W2098841537","https://openalex.org/W2104290444","https://openalex.org/W2124509324","https://openalex.org/W2147898188","https://openalex.org/W2172000360","https://openalex.org/W2319358180","https://openalex.org/W2594639291","https://openalex.org/W2761726598","https://openalex.org/W2962957673","https://openalex.org/W2997701990","https://openalex.org/W3018189936","https://openalex.org/W6637179743","https://openalex.org/W6674632333","https://openalex.org/W6675747103"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W2357523926"],"abstract_inverted_index":{"In":[0,12],"this":[1],"paper,":[2],"we":[3,78,100],"address":[4],"the":[5,67,70,83,89,94,97,108],"scalability":[6,30],"issue":[7],"of":[8,69,96],"graph-based":[9,15],"semi-supervised":[10,16],"learnings.":[11],"recent":[13],"years,":[14],"learnings":[17],"using":[18],"anchor":[19,23,56,71,75],"graphs":[20,24],"and":[21,38],"hierarchical":[22,55,74],"have":[25],"been":[26],"proposed":[27,60,98],"as":[28],"high":[29],"approaches.":[31],"However,":[32],"these":[33],"techniques":[34],"utilize":[35],"linear":[36],"predictor":[37],"cannot":[39],"infer":[40],"to":[41,52,87,112],"unknown":[42],"data.":[43],"We":[44],"propose":[45],"a":[46,54,63],"Laplacian":[47],"regularized":[48],"least":[49],"squares":[50],"classification":[51],"assume":[53],"graph":[57,72],"(LapRLSC-HAG).":[58],"The":[59],"method":[61],"reduces":[62],"memory":[64],"pressure":[65],"by":[66],"property":[68],"or":[73],"graph.":[76],"Furthermore,":[77],"present":[79],"two":[80],"strategies":[81],"optimizing":[82],"primal":[84],"LapRLSC-HAG":[85],"problems":[86],"reduce":[88],"computational":[90],"complexity.":[91],"To":[92],"demonstrate":[93],"effectiveness":[95],"method,":[99],"make":[101],"experimental":[102],"evaluations":[103],"on":[104],"data":[105],"sets":[106],"varying":[107],"size":[109],"from":[110],"thousands":[111],"one":[113],"million.":[114]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}