{"id":"https://openalex.org/W2897062831","doi":"https://doi.org/10.1109/sera.2018.8477214","title":"Least-Squares Support Vector Machine for Semi-Supervised Multi-Tasking","display_name":"Least-Squares Support Vector Machine for Semi-Supervised Multi-Tasking","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2897062831","doi":"https://doi.org/10.1109/sera.2018.8477214","mag":"2897062831"},"language":"en","primary_location":{"id":"doi:10.1109/sera.2018.8477214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sera.2018.8477214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","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/A5084452333","display_name":"Xuekuo Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuekuo Jia","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081191314","display_name":"Shipu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shipu Wang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100675701","display_name":"Yun Yang","orcid":"https://orcid.org/0000-0002-9893-3436"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Yang","raw_affiliation_strings":["School of Software, Yunnan University, Kunming, China"],"affiliations":[{"raw_affiliation_string":"School of Software, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084452333"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.55900939,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"86"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.992900013923645,"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/T12676","display_name":"Machine Learning and ELM","score":0.9909999966621399,"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/support-vector-machine","display_name":"Support vector machine","score":0.8228640556335449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7768638730049133},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6414515376091003},{"id":"https://openalex.org/keywords/least-squares-support-vector-machine","display_name":"Least squares support vector machine","score":0.6196973919868469},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5990374088287354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5962398648262024},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.5143821835517883},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.46113836765289307},{"id":"https://openalex.org/keywords/reset","display_name":"Reset (finance)","score":0.4552220106124878},{"id":"https://openalex.org/keywords/structured-support-vector-machine","display_name":"Structured support vector machine","score":0.4450066089630127},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.42351460456848145},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4180283546447754},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.41200560331344604},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.41129976511001587},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.326923131942749},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10731881856918335},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.07142600417137146},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06730091571807861},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06676164269447327}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8228640556335449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7768638730049133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6414515376091003},{"id":"https://openalex.org/C145828037","wikidata":"https://www.wikidata.org/wiki/Q17086219","display_name":"Least squares support vector machine","level":3,"score":0.6196973919868469},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5990374088287354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5962398648262024},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.5143821835517883},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.46113836765289307},{"id":"https://openalex.org/C2779795794","wikidata":"https://www.wikidata.org/wiki/Q7315343","display_name":"Reset (finance)","level":2,"score":0.4552220106124878},{"id":"https://openalex.org/C125168437","wikidata":"https://www.wikidata.org/wiki/Q7625184","display_name":"Structured support vector machine","level":3,"score":0.4450066089630127},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.42351460456848145},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4180283546447754},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.41200560331344604},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.41129976511001587},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.326923131942749},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10731881856918335},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.07142600417137146},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06730091571807861},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06676164269447327},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sera.2018.8477214","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sera.2018.8477214","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA)","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":39,"referenced_works":["https://openalex.org/W1511216419","https://openalex.org/W1596717185","https://openalex.org/W1988748730","https://openalex.org/W2004083143","https://openalex.org/W2045106581","https://openalex.org/W2057068800","https://openalex.org/W2065180801","https://openalex.org/W2110994494","https://openalex.org/W2117130368","https://openalex.org/W2123422288","https://openalex.org/W2133491790","https://openalex.org/W2143104527","https://openalex.org/W2144752499","https://openalex.org/W2148522164","https://openalex.org/W2150775571","https://openalex.org/W2150890437","https://openalex.org/W2151732775","https://openalex.org/W2155916898","https://openalex.org/W2160727143","https://openalex.org/W2187552161","https://openalex.org/W2338231020","https://openalex.org/W2356481047","https://openalex.org/W2362386422","https://openalex.org/W2379258515","https://openalex.org/W2618317993","https://openalex.org/W2742079690","https://openalex.org/W2769674252","https://openalex.org/W2794937634","https://openalex.org/W2913340405","https://openalex.org/W2928720868","https://openalex.org/W3209042722","https://openalex.org/W4285719527","https://openalex.org/W6636406500","https://openalex.org/W6676678553","https://openalex.org/W6682713862","https://openalex.org/W6682783130","https://openalex.org/W6683734941","https://openalex.org/W6738416923","https://openalex.org/W7033346528"],"related_works":["https://openalex.org/W2122277321","https://openalex.org/W1678040990","https://openalex.org/W2769345709","https://openalex.org/W2178308471","https://openalex.org/W2023602538","https://openalex.org/W2315850941","https://openalex.org/W2350916155","https://openalex.org/W2360756200","https://openalex.org/W2071357642","https://openalex.org/W2913120735"],"abstract_inverted_index":{"The":[0,166],"semi-supervised":[1,80,88],"multi-tasking":[2,89],"using":[3,13,91,123],"least-squares":[4,92,103],"support":[5,35,39,75,93,104],"vector":[6,36,40,76,94,105],"machine":[7,41,77,106],"can":[8],"further":[9],"improve":[10,131],"performance":[11],"by":[12],"related":[14,17,98,128],"information":[15,126],"of":[16,24,31,56,119,134,155,175],"tasks,":[18],"and":[19,28,47,66,85,113,122,144,160],"it":[20,48],"inherits":[21],"the":[22,32,83,117,124,132,138,141,145,153,162,169,173,176],"advantages":[23],"high":[25,29],"training":[26,61,139],"speed":[27],"efficiency":[30,133],"least":[33,73],"square":[34],"machine.":[37,95],"Standard":[38],"is":[42,49,64,107],"based":[43,78],"on":[44,79,97,168],"supervised":[45],"learning,":[46],"necessary":[50],"to":[51,82,109,130,151,157],"manually":[52],"mark":[53],"large":[54],"amounts":[55],"data":[57],"for":[58],"obtaining":[59],"sufficient":[60],"data,":[62],"which":[63],"costly":[65],"inefficient.":[67],"In":[68,137],"this":[69],"paper,":[70],"we":[71],"apply":[72],"squares":[74],"learning":[81,100],"multi-tasks":[84],"propose":[86],"a":[87],"approach":[90],"Based":[96],"tasks":[99,129],"simultaneously,":[101],"multi-task":[102],"used":[108,150],"train":[110],"both":[111],"labeled":[112],"unlabeled":[114],"samples,":[115],"overcoming":[116],"limitation":[118],"slow":[120],"training,":[121],"useful":[125],"among":[127],"all":[135],"tasks.":[136],"process,":[140],"regional":[142],"tagging":[143],"tag":[146],"reset":[147],"methods":[148],"are":[149],"reduce":[152],"number":[154],"iterations":[156],"achieve":[158],"convergence":[159],"increases":[161],"fault":[163],"tolerance":[164],"rate.":[165],"experiment":[167],"actual":[170],"dataset":[171],"shows":[172],"effectiveness":[174],"approach.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
