{"id":"https://openalex.org/W1989946722","doi":"https://doi.org/10.1145/2661829.2662091","title":"Multi-task Sparse Structure Learning","display_name":"Multi-task Sparse Structure Learning","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W1989946722","doi":"https://doi.org/10.1145/2661829.2662091","mag":"1989946722"},"language":"en","primary_location":{"id":"doi:10.1145/2661829.2662091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1409.0272","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001741874","display_name":"Andr\u00e9 Gon\u00e7alves","orcid":"https://orcid.org/0000-0002-0320-280X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andre R. Goncalves","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104315751","display_name":"Puja Das","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Puja Das","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008488006","display_name":"Soumyadeep Chatterjee","orcid":"https://orcid.org/0000-0001-7957-1727"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soumyadeep Chatterjee","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065716820","display_name":"V. Sivakumar","orcid":"https://orcid.org/0000-0001-9910-726X"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidyashankar Sivakumar","raw_affiliation_strings":["University of Minnesota, Minneapolis, MN, USA",", University of Minnesota, Minneapolis, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":", University of Minnesota, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035858702","display_name":"Fernando J. Von Zuben","orcid":"https://orcid.org/0000-0002-4128-5415"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fernando J. Von Zuben","raw_affiliation_strings":["University of Campinas, Campinas, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Campinas, Campinas, Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014459472","display_name":"Arindam Banerjee","orcid":"https://orcid.org/0000-0002-7856-5699"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam Banerjee","raw_affiliation_strings":["University of Minnesota, Twin Cities, Minneapolis, MN, USA","University of Minnesota, Twin Cities, Minneapolis, MN, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Twin Cities, Minneapolis, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]},{"raw_affiliation_string":"University of Minnesota, Twin Cities, Minneapolis, MN, USA#TAB#","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5001741874"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":null,"apc_paid":null,"fwci":6.3651,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.96439615,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"451","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9944999814033508,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9944999814033508,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12368","display_name":"Grey System Theory Applications","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7153892517089844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7018837332725525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6509779095649719},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.5807807445526123},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5325920581817627},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5210587382316589},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5144391655921936},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.48003852367401123},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.45362889766693115},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.4430635869503021},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4104973375797272},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16931450366973877},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09358733892440796}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7153892517089844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7018837332725525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6509779095649719},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.5807807445526123},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5325920581817627},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5210587382316589},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5144391655921936},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.48003852367401123},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.45362889766693115},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.4430635869503021},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4104973375797272},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16931450366973877},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09358733892440796},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2661829.2662091","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662091","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1409.0272","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.0272","pdf_url":"https://arxiv.org/pdf/1409.0272","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.741.6023","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.741.6023","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1409.0272.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1409.0272","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.0272","pdf_url":"https://arxiv.org/pdf/1409.0272","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.8600000143051147,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G3340519626","display_name":null,"funder_award_id":"IIS-1029711 IIS-0916750 IIS-0953274 CNS-1314560 IIS-1422557","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"},{"id":"https://openalex.org/G5614774848","display_name":null,"funder_award_id":"IIS-1029711 IIS-0916750 IIS-0953274 CNS-1314560 IIS-1422557","funder_id":"https://openalex.org/F4320337388","funder_display_name":"Division of Computer and Network Systems"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320337388","display_name":"Division of Computer and Network Systems","ror":"https://ror.org/02rdzmk74"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W183287438","https://openalex.org/W1480376833","https://openalex.org/W1497745584","https://openalex.org/W1554944419","https://openalex.org/W1614862348","https://openalex.org/W1639316992","https://openalex.org/W1648933886","https://openalex.org/W1990376608","https://openalex.org/W1998635907","https://openalex.org/W2001672825","https://openalex.org/W2003602579","https://openalex.org/W2006750690","https://openalex.org/W2010824638","https://openalex.org/W2024966118","https://openalex.org/W2049076973","https://openalex.org/W2060624994","https://openalex.org/W2095938605","https://openalex.org/W2100556411","https://openalex.org/W2111561248","https://openalex.org/W2114551781","https://openalex.org/W2118099552","https://openalex.org/W2119187866","https://openalex.org/W2126288184","https://openalex.org/W2131479143","https://openalex.org/W2132555912","https://openalex.org/W2139314206","https://openalex.org/W2143104527","https://openalex.org/W2144752499","https://openalex.org/W2149620660","https://openalex.org/W2150002853","https://openalex.org/W2151128232","https://openalex.org/W2159514083","https://openalex.org/W2161733758","https://openalex.org/W2164278908","https://openalex.org/W2165644552","https://openalex.org/W2166721725","https://openalex.org/W2171033594","https://openalex.org/W2321476236","https://openalex.org/W2397220982","https://openalex.org/W2416564997","https://openalex.org/W2562162676","https://openalex.org/W2584850978","https://openalex.org/W2801490189","https://openalex.org/W2912994366","https://openalex.org/W2964121793","https://openalex.org/W3010453621","https://openalex.org/W3015299830","https://openalex.org/W3098834468","https://openalex.org/W3209042722","https://openalex.org/W4206535445","https://openalex.org/W4234149415","https://openalex.org/W4241015643","https://openalex.org/W4242176936","https://openalex.org/W4252317510","https://openalex.org/W4285719527","https://openalex.org/W4292363360","https://openalex.org/W4300917500","https://openalex.org/W4302388043","https://openalex.org/W6636960831","https://openalex.org/W6676752471","https://openalex.org/W6681822384","https://openalex.org/W6684360038","https://openalex.org/W6684671274","https://openalex.org/W6731047904","https://openalex.org/W6750773745","https://openalex.org/W6819510131","https://openalex.org/W6858008074","https://openalex.org/W7028471627"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W2109986081","https://openalex.org/W3162204513","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4297589944","https://openalex.org/W2417308975","https://openalex.org/W4385769873","https://openalex.org/W2964129930","https://openalex.org/W4281634296"],"abstract_inverted_index":{"Multi-task":[0],"learning":[1,9,54,88,96],"(MTL)":[2],"aims":[3],"to":[4,27,47],"improve":[5],"generalization":[6],"performance":[7],"by":[8],"multiple":[10],"related":[11],"tasks":[12],"simultaneously.":[13],"While":[14],"sometimes":[15],"the":[16,24,55,69,74,106,113,116,134,157,165],"underlying":[17],"task":[18,58,70,76,85],"relationship":[19,71,86],"structure":[20,25,56,72,87,95],"is":[21,79],"known,":[22],"often":[23],"needs":[26],"be":[28],"estimated":[29],"from":[30],"data":[31],"at":[32],"hand.":[33],"In":[34,60],"this":[35],"paper,":[36],"we":[37,62],"present":[38],"a":[39,64,120],"novel":[40],"family":[41],"of":[42,53,57,68,97,105,115,122,136,144],"models":[43,100],"for":[44,127,141,164],"MTL,":[45],"applicable":[46],"regression":[48,128],"and":[49,73,124,129,154],"classification":[50],"problems,":[51],"capable":[52],"relationships.":[59],"particular,":[61],"consider":[63,133],"joint":[65],"estimation":[66],"problem":[67,135],"individual":[75],"parameters,":[77],"which":[78],"solved":[80],"using":[81],"alternating":[82],"minimization.":[83],"The":[84],"component":[89],"builds":[90],"on":[91,102,119,149],"recent":[92],"advances":[93],"in":[94,151],"Gaussian":[98],"graphical":[99],"based":[101],"sparse":[103],"estimators":[104],"precision":[107],"(inverse":[108],"covariance)":[109],"matrix.":[110],"We":[111,131],"illustrate":[112],"effectiveness":[114],"proposed":[117,158],"model":[118,139,159],"variety":[121],"synthetic":[123],"benchmark":[125],"datasets":[126],"classification.":[130],"also":[132],"combining":[137],"climate":[138],"outputs":[140],"better":[142],"projections":[143],"future":[145],"climate,":[146],"with":[147],"focus":[148],"temperature":[150],"South":[152],"America,":[153],"show":[155],"that":[156],"outperforms":[160],"several":[161],"existing":[162],"methods":[163],"problem.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
