{"id":"https://openalex.org/W2741807795","doi":"https://doi.org/10.24963/ijcai.2017/337","title":"Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression","display_name":"Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2741807795","doi":"https://doi.org/10.24963/ijcai.2017/337","mag":"2741807795"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/337","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Adaptive_semi-supervised_learning_with_discriminative_least_squares_regression/27592272","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013911439","display_name":"Minnan Luo","orcid":"https://orcid.org/0000-0002-0140-7860"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minnan Luo","raw_affiliation_strings":["MOEKLINNS Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOEKLINNS Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384144","display_name":"Lingling Zhang","orcid":"https://orcid.org/0000-0001-8136-8795"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingling Zhang","raw_affiliation_strings":["SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003222421","display_name":"Feiping Nie","orcid":"https://orcid.org/0000-0002-0871-6519"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiping Nie","raw_affiliation_strings":["School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an 710072, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an 710072, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034967388","display_name":"Xiaojun Chang","orcid":"https://orcid.org/0000-0002-7778-8807"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojun Chang","raw_affiliation_strings":["School of Computer Science, Carnegie Mellon University, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Carnegie Mellon University, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074506574","display_name":"Buyue Qian","orcid":"https://orcid.org/0000-0003-4780-5677"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Buyue Qian","raw_affiliation_strings":["SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041083459","display_name":"Qinghua Zheng","orcid":"https://orcid.org/0000-0002-8436-4754"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Zheng","raw_affiliation_strings":["MOEKLINNS Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOEKLINNS Lab, Department of Computer Science, Xi'an Jiaotong University, Shaanxi, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2727,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.90364706,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2421","last_page":"2427"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9955999851226807,"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":0.9955999851226807,"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/T12676","display_name":"Machine Learning and ELM","score":0.9768999814987183,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9735000133514404,"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/discriminative-model","display_name":"Discriminative model","score":0.7237256765365601},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.639065146446228},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.605570375919342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5609378814697266},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5538691282272339},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5402516722679138},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.526431679725647},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5098344683647156},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5019726753234863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4835922122001648},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4791414141654968},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.45880475640296936},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4352809190750122},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3377705216407776},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12461191415786743},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10971054434776306}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7237256765365601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.639065146446228},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.605570375919342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5609378814697266},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5538691282272339},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5402516722679138},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.526431679725647},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5098344683647156},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5019726753234863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4835922122001648},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4791414141654968},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.45880475640296936},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4352809190750122},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3377705216407776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12461191415786743},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10971054434776306},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2017/337","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:figshare.com:article/27592272","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Adaptive_semi-supervised_learning_with_discriminative_least_squares_regression/27592272","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Conference contribution"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/27592272","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Adaptive_semi-supervised_learning_with_discriminative_least_squares_regression/27592272","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Conference contribution"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1990334093","https://openalex.org/W2008989859","https://openalex.org/W2043080228","https://openalex.org/W2044544672","https://openalex.org/W2104290444","https://openalex.org/W2113590298","https://openalex.org/W2115694019","https://openalex.org/W2118670840","https://openalex.org/W2122565017","https://openalex.org/W2123921160","https://openalex.org/W2128097790","https://openalex.org/W2128333053","https://openalex.org/W2135496738","https://openalex.org/W2139823104","https://openalex.org/W2154455818","https://openalex.org/W2155759509","https://openalex.org/W2163584563","https://openalex.org/W2167999447","https://openalex.org/W2244035566","https://openalex.org/W2246035736","https://openalex.org/W2590822257","https://openalex.org/W2997701990","https://openalex.org/W3148981562","https://openalex.org/W4302332486"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W3130163047","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263"],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1],"plays":[2],"a":[3,10,45,84],"significant":[4,56],"role":[5],"in":[6],"multi-class":[7,113,173],"classification,":[8,81],"where":[9],"small":[11],"number":[12],"of":[13,38,58,65,73,120,152,168],"labeled":[14,39,59],"data":[15,22,43,60],"are":[16,104],"more":[17],"deterministic":[18],"while":[19],"substantial":[20],"unlabeled":[21,41,66],"might":[23],"cause":[24],"large":[25],"uncertainties":[26],"and":[27,40,61,110,150,166],"potential":[28],"threats.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,82],"distinguish":[34],"the":[35,55,63,108,117,134,148,153,164,169],"label":[36,91],"fitting":[37],"training":[42],"through":[44],"probabilistic":[46],"vector":[47],"with":[48,92,137],"an":[49,93],"adaptive":[50],"parameter,":[51],"which":[52],"always":[53],"ensures":[54],"importance":[57],"characterizes":[62],"contribution":[64],"instance":[67],"according":[68],"to":[69,123,132],"its":[70],"uncertainty.":[71],"Instead":[72],"using":[74],"traditional":[75],"least":[76],"squares":[77],"regression":[78],"(LSR)":[79],"for":[80,141,172],"develop":[83],"new":[85],"discriminative":[86],"LSR":[87],"by":[88,115],"equipping":[89],"each":[90,142],"adjustment":[94],"vector.":[95],"This":[96],"strategy":[97],"avoids":[98],"incorrect":[99],"penalization":[100],"on":[101,159],"samples":[102],"that":[103],"far":[105],"away":[106],"from":[107],"boundary":[109],"simultaneously":[111],"facilitates":[112],"classification":[114,174],"enlarging":[116],"geometrical":[118],"distance":[119],"instances":[121],"belonging":[122],"different":[124],"classes.":[125],"An":[126],"efficient":[127],"alternative":[128],"algorithm":[129,155],"is":[130],"exploited":[131],"solve":[133],"proposed":[135,154,170],"model":[136,171],"closed":[138],"form":[139],"solution":[140],"updating":[143],"rule.":[144],"We":[145],"also":[146],"analyze":[147],"convergence":[149],"complexity":[151],"theoretically.":[156],"Experimental":[157],"results":[158],"several":[160],"benchmark":[161],"datasets":[162],"demonstrate":[163],"effectiveness":[165],"superiority":[167],"tasks.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2025-10-10T00:00:00"}
