{"id":"https://openalex.org/W7138384333","doi":"https://doi.org/10.1609/aaai.v40i28.39487","title":"Semi-Supervised Regression by Preserving Ranking Relationships Between Close Unlabeled Samples","display_name":"Semi-Supervised Regression by Preserving Ranking Relationships Between Close Unlabeled Samples","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138384333","doi":"https://doi.org/10.1609/aaai.v40i28.39487"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i28.39487","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i28.39487","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39487/43448","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39487/43448","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088686727","display_name":"X. LI","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108141","display_name":"Ministry of Education","ror":"https://ror.org/01hw7wf62","country_code":"IR","type":"government","lineage":["https://openalex.org/I4210108141"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Ximing Li","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China\nRIKEN Center for Advanced Intelligence Project, Japan"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China\nRIKEN Center for Advanced Intelligence Project, Japan","institution_ids":["https://openalex.org/I4210108141"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129745004","display_name":"Jiaxuan Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxuan Jiang","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129648795","display_name":"Changchun Li","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changchun Li","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129660472","display_name":"You Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137766","display_name":"Institute for Advanced Study","ror":"https://ror.org/03xg85719","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210137766"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"You Lu","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology, China"],"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology, China","institution_ids":["https://openalex.org/I4210137766"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129729387","display_name":"Renchu Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renchu Guan","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, China\nKey Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, Jilin University, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5088686727"],"corresponding_institution_ids":["https://openalex.org/I4210108141"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.56065901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"28","first_page":"23195","last_page":"23203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9419999718666077,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9419999718666077,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.015300000086426735,"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":0.008799999952316284,"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/ranking","display_name":"Ranking (information retrieval)","score":0.7555000185966492},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6870999932289124},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5845000147819519},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5759999752044678},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5236999988555908},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4596000015735626},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4569000005722046},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.42340001463890076},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4077000021934509}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7555000185966492},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6870999932289124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6262999773025513},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5845000147819519},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5587999820709229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5529000163078308},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5236999988555908},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4569000005722046},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.42340001463890076},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.40149998664855957},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.352400004863739},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3278999924659729},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.326200008392334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32030001282691956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C17418463","wikidata":"https://www.wikidata.org/wiki/Q3455874","display_name":"Isotonic regression","level":3,"score":0.30379998683929443},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C72169020","wikidata":"https://www.wikidata.org/wiki/Q194404","display_name":"Monotonic function","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i28.39487","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i28.39487","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39487/43448","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i28.39487","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i28.39487","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39487/43448","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/G5962297099","display_name":null,"funder_award_id":"2021ZD0112500","funder_id":"https://openalex.org/F4320329860","funder_display_name":"National Science and Technology Major Project"},{"id":"https://openalex.org/G8513333314","display_name":null,"funder_award_id":"2021ZD01","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8897825800","display_name":null,"funder_award_id":"62276113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138384333.pdf","grobid_xml":"https://content.openalex.org/works/W7138384333.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Semi-Supervised":[0,49,94],"Learning":[1],"(SSL)":[2],"aims":[3],"to":[4,88,122,127,135],"improve":[5,128],"the":[6,58,123,137,152],"learning":[7,11],"performance":[8,138],"of":[9,16,60,139],"supervised":[10],"with":[12,31,79,111],"a":[13,65,89,115],"large":[14],"number":[15],"unlabeled":[17,29],"samples.":[18],"The":[19],"existing":[20,153],"SSL":[21],"methods":[22],"such":[23],"as":[24],"FixMatch":[25],"and":[26,34,41,118,144],"FlexMatch":[27],"select":[28],"samples":[30,110],"high-confident":[32,80,112],"pseudo-labels":[33],"make":[35],"consistency":[36],"constraints":[37],"between":[38],"their":[39],"weak":[40],"strong":[42],"augmentations.":[43],"Unfortunately,":[44],"they":[45],"cannot":[46],"be":[47],"applied":[48],"Regression":[50,95],"(SSR)":[51],"because":[52],"regression":[53,129],"predictions":[54],"can":[55,150],"not":[56],"reflect":[57],"confidence":[59],"pseudo-labels.":[61],"To":[62],"solve":[63],"this,":[64],"recent":[66],"SSR":[67,91],"method":[68],"RankUp":[69],"incorporates":[70],"an":[71],"auxiliary":[72,124],"ranking":[73,125],"task":[74,126],"by":[75,96],"leveraging":[76],"sample":[77],"pairs":[78],"pseudo-ranks.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"upgrade":[86],"Rankup":[87],"novel":[90],"method,":[92],"namely":[93],"Ranking":[97],"Close":[98],"Unlabeled":[99],"Samples":[100],"(SSR-RCUS).":[101],"Its":[102],"basic":[103],"idea":[104],"is":[105],"reconstructing":[106],"closed":[107],"mixup":[108],"augmented":[109],"pseudo-ranks":[113],"under":[114],"monotonicity":[116],"assumption,":[117],"then":[119],"applying":[120],"them":[121],"performance.":[130],"We":[131],"conduct":[132],"extensive":[133],"experiments":[134],"evaluate":[136],"SSR-RCUS":[140,149],"on":[141],"benchmark":[142],"datasets,":[143],"empirical":[145],"results":[146],"demonstrate":[147],"that":[148],"outperform":[151],"baselines":[154],"in":[155],"various":[156],"settings,":[157],"especially":[158],"when":[159],"labeled":[160],"data":[161],"are":[162],"scarce.":[163]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-03-18T00:00:00"}