{"id":"https://openalex.org/W2593607551","doi":"https://doi.org/10.1109/tcyb.2017.2670608","title":"Optimizing Evaluation Metrics for Multitask Learning via the Alternating Direction Method of Multipliers","display_name":"Optimizing Evaluation Metrics for Multitask Learning via the Alternating Direction Method of Multipliers","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2593607551","doi":"https://doi.org/10.1109/tcyb.2017.2670608","mag":"2593607551","pmid":"https://pubmed.ncbi.nlm.nih.gov/28362621"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2017.2670608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2017.2670608","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5068028421","display_name":"Ge-Yang Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ge-Yang Ke","raw_affiliation_strings":["School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087294951","display_name":"Yan Pan","orcid":"https://orcid.org/0000-0002-0466-3763"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Pan","raw_affiliation_strings":["School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017205177","display_name":"Jian Yin","orcid":"https://orcid.org/0000-0002-1214-5384"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yin","raw_affiliation_strings":["School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Data Science and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108051852","display_name":"Changqin Huang","orcid":"https://orcid.org/0000-0003-1371-2608"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang-Qin Huang","raw_affiliation_strings":["School of Information Technology in Education, South China Normal University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Technology in Education, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068028421"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.9604,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71900479,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"48","issue":"3","first_page":"993","last_page":"1006"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.994700014591217,"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/computer-science","display_name":"Computer science","score":0.5900905728340149},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.5339938998222351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42589226365089417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3436805009841919},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13623717427253723},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.11408856511116028}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5900905728340149},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.5339938998222351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42589226365089417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3436805009841919},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13623717427253723},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.11408856511116028},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2017.2670608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2017.2670608","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:28362621","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28362621","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1751367930","display_name":null,"funder_award_id":"2014A030313154","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G3024991072","display_name":null,"funder_award_id":"61472455","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4044104431","display_name":null,"funder_award_id":"U1401256","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4883015174","display_name":null,"funder_award_id":"2016YFB0201900","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5229126207","display_name":null,"funder_award_id":"61472453","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6221921357","display_name":null,"funder_award_id":"61370021","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6839310337","display_name":null,"funder_award_id":"61370229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8698608195","display_name":null,"funder_award_id":"U1501252","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/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W182881619","https://openalex.org/W201974436","https://openalex.org/W1497745584","https://openalex.org/W1546425806","https://openalex.org/W1736339626","https://openalex.org/W1871180460","https://openalex.org/W1975892281","https://openalex.org/W1977617632","https://openalex.org/W1986080131","https://openalex.org/W1995372246","https://openalex.org/W1998635907","https://openalex.org/W1999954155","https://openalex.org/W2002917851","https://openalex.org/W2018096278","https://openalex.org/W2029517229","https://openalex.org/W2032612424","https://openalex.org/W2040649920","https://openalex.org/W2049953412","https://openalex.org/W2053463056","https://openalex.org/W2065180801","https://openalex.org/W2069936846","https://openalex.org/W2070771761","https://openalex.org/W2076422387","https://openalex.org/W2097154431","https://openalex.org/W2103972604","https://openalex.org/W2104265493","https://openalex.org/W2105180921","https://openalex.org/W2118152081","https://openalex.org/W2118585731","https://openalex.org/W2123432324","https://openalex.org/W2127176025","https://openalex.org/W2127615881","https://openalex.org/W2130903752","https://openalex.org/W2132345820","https://openalex.org/W2136920242","https://openalex.org/W2136979193","https://openalex.org/W2137107481","https://openalex.org/W2138290126","https://openalex.org/W2142681791","https://openalex.org/W2144752499","https://openalex.org/W2148522164","https://openalex.org/W2164278908","https://openalex.org/W2166267120","https://openalex.org/W2186054958","https://openalex.org/W2293824885","https://openalex.org/W2405493940","https://openalex.org/W2429914308","https://openalex.org/W2913340405","https://openalex.org/W3008214279","https://openalex.org/W4252684946","https://openalex.org/W4292363360","https://openalex.org/W6603183647","https://openalex.org/W6608209381","https://openalex.org/W6629935912","https://openalex.org/W6632714361","https://openalex.org/W6675892227","https://openalex.org/W6677419484","https://openalex.org/W6677656871","https://openalex.org/W6679734692","https://openalex.org/W6680389645","https://openalex.org/W6680576647","https://openalex.org/W6681414149","https://openalex.org/W6686819018","https://openalex.org/W6697060382","https://openalex.org/W6714140905"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4312192474","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Multitask":[0],"learning":[1],"(MTL)":[2],"aims":[3],"to":[4,30,42,64,105,123,175,182],"improve":[5],"the":[6,14,25,32,45,51,67,87,97,107,158,167,176,183,194,202,226,240],"generalization":[7],"performance":[8,237],"of":[9,34,74,79,89,109,116,126,141,162,191,223,230],"multiple":[10,117],"tasks":[11,111],"by":[12],"exploiting":[13],"shared":[15],"factors":[16],"among":[17],"them.":[18],"Various":[19],"metrics":[20,69,85,234],"(e.g.,":[21],"-score,":[22],"area":[23],"under":[24],"ROC":[26],"curve)":[27],"are":[28,144],"used":[29],"evaluate":[31],"performances":[33],"MTL":[35,39,75,80,192,224,228],"methods.":[36,243],"Most":[37],"existing":[38],"methods":[40],"try":[41],"minimize":[43],"either":[44],"misclassified":[46],"errors":[47,54],"for":[48,55,70],"classification":[49],"or":[50],"mean":[52],"squared":[53],"regression.":[56],"In":[57],"this":[58,148],"paper,":[59],"we":[60,150,165,205],"propose":[61,151,206],"a":[62,71,93,114,124,152,172,188,220],"method":[63,229],"directly":[65,82,231],"optimize":[66],"evaluation":[68,84,128,215,233],"large":[72,189,221],"family":[73,190,222],"problems.":[76],"The":[77],"formulation":[78,134],"that":[81],"optimizes":[83],"is":[86,135],"combination":[88],"two":[90],"parts:":[91],"1)":[92],"regularizer":[94,177],"defined":[95],"on":[96,130,157],"weight":[98],"matrix":[99],"over":[100],"all":[101],"tasks,":[102],"in":[103,137,219],"order":[104],"capture":[106],"relatedness":[108],"these":[110],"and":[112,178],"2)":[113],"sum":[115],"structured":[118,184],"hinge":[119,185],"losses,":[120],"each":[121],"corresponding":[122,174,181,241],"surrogate":[125],"some":[127],"metric":[129],"one":[131],"task.":[132],"This":[133],"challenging":[136],"optimization":[138,154,169,232],"because":[139],"both":[140],"its":[142],"parts":[143],"nonsmooth.":[145],"To":[146,200],"tackle":[147],"issue,":[149],"novel":[153],"procedure":[155],"based":[156],"alternating":[159],"direction":[160],"scheme":[161],"multipliers,":[163],"where":[164],"decompose":[166],"whole":[168],"problem":[170],"into":[171],"subproblem":[173,180,196],"another":[179],"losses.":[186],"For":[187],"problems,":[193,225],"first":[195],"has":[197,235],"closed-form":[198],"solutions.":[199],"solve":[201],"second":[203],"subproblem,":[204],"an":[207],"efficient":[208],"primal-dual":[209],"algorithm":[210],"via":[211],"coordinate":[212],"ascent.":[213],"Extensive":[214],"results":[216],"demonstrate":[217],"that,":[218],"proposed":[227],"superior":[236],"gains":[238],"against":[239],"baseline":[242]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
