{"id":"https://openalex.org/W2034295546","doi":"https://doi.org/10.1145/2086737.2086742","title":"Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks","display_name":"Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks","publication_year":2012,"publication_date":"2012-01-31","ids":{"openalex":"https://openalex.org/W2034295546","doi":"https://doi.org/10.1145/2086737.2086742","mag":"2034295546","pmid":"https://pubmed.ncbi.nlm.nih.gov/24077658"},"language":"en","primary_location":{"id":"doi:10.1145/2086737.2086742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2086737.2086742","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5100765308","display_name":"Jianhui Chen","orcid":"https://orcid.org/0000-0001-7954-3574"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jianhui Chen","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396338","display_name":"Ji Liu","orcid":"https://orcid.org/0000-0003-2871-9888"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ji Liu","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010419481","display_name":"Jieping Ye","orcid":"https://orcid.org/0000-0001-8662-5818"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jieping Ye","raw_affiliation_strings":["Arizona State University"],"affiliations":[{"raw_affiliation_string":"Arizona State University","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100765308"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":18.8868,"has_fulltext":false,"cited_by_count":144,"citation_normalized_percentile":{"value":0.99602276,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"5","issue":"4","first_page":"1","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"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":1.0,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9708999991416931,"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/proximal-gradient-methods","display_name":"Proximal Gradient Methods","score":0.7107004523277283},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6044301390647888},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5507786870002747},{"id":"https://openalex.org/keywords/gradient-method","display_name":"Gradient method","score":0.5182806849479675},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5088387131690979},{"id":"https://openalex.org/keywords/trust-region","display_name":"Trust region","score":0.48982855677604675},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.4764000475406647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4674810767173767},{"id":"https://openalex.org/keywords/stationary-point","display_name":"Stationary point","score":0.4449229836463928},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.44031766057014465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43963080644607544},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.41286277770996094},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4021797776222229},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.34080177545547485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2059551477432251}],"concepts":[{"id":"https://openalex.org/C10494615","wikidata":"https://www.wikidata.org/wiki/Q17086765","display_name":"Proximal Gradient Methods","level":4,"score":0.7107004523277283},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6044301390647888},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5507786870002747},{"id":"https://openalex.org/C115680565","wikidata":"https://www.wikidata.org/wiki/Q5977448","display_name":"Gradient method","level":2,"score":0.5182806849479675},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5088387131690979},{"id":"https://openalex.org/C89109886","wikidata":"https://www.wikidata.org/wiki/Q1535924","display_name":"Trust region","level":3,"score":0.48982855677604675},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4764000475406647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4674810767173767},{"id":"https://openalex.org/C189237950","wikidata":"https://www.wikidata.org/wiki/Q2500758","display_name":"Stationary point","level":2,"score":0.4449229836463928},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.44031766057014465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43963080644607544},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.41286277770996094},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4021797776222229},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.34080177545547485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2059551477432251},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C178635117","wikidata":"https://www.wikidata.org/wiki/Q747499","display_name":"RADIUS","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1145/2086737.2086742","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2086737.2086742","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},{"id":"pmid:24077658","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/24077658","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":"ACM transactions on knowledge discovery from data","raw_type":null},{"id":"pmh:oai:europepmc.org:2772566","is_oa":false,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3783291","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"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:10.1.1.172.2471","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.172.2471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.public.asu.edu/%7Ejye02/Publications/Papers/rp701c-chen.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.416.1048","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.416.1048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://pages.cs.wisc.edu/~ji-liu/paper/Jianhui-Ji-KDD10.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.416.7163","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.416.7163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://pages.cs.wisc.edu/~ji-liu/paper/Jianhui-Ji-TKDD.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5900747426","display_name":null,"funder_award_id":"IIS-0812551IIS-0953662CCF-1025177","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"},{"id":"https://openalex.org/G5905345011","display_name":null,"funder_award_id":"LM010730","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G865305594","display_name":null,"funder_award_id":"IIS-0812551IIS-0953662CCF-1025177","funder_id":"https://openalex.org/F4320337387","funder_display_name":"Division of Computing and Communication Foundations"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337387","display_name":"Division of Computing and Communication Foundations","ror":"https://ror.org/01mng8331"},{"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":65,"referenced_works":["https://openalex.org/W3219084","https://openalex.org/W64096456","https://openalex.org/W1497745584","https://openalex.org/W1497826971","https://openalex.org/W1550965000","https://openalex.org/W1560724230","https://openalex.org/W1599271073","https://openalex.org/W1648933886","https://openalex.org/W1769664844","https://openalex.org/W1871180460","https://openalex.org/W1966096622","https://openalex.org/W1967073510","https://openalex.org/W1968398095","https://openalex.org/W1986744686","https://openalex.org/W1998635907","https://openalex.org/W2029213856","https://openalex.org/W2029970906","https://openalex.org/W2030290736","https://openalex.org/W2045704273","https://openalex.org/W2065180801","https://openalex.org/W2081385752","https://openalex.org/W2097260978","https://openalex.org/W2100556411","https://openalex.org/W2115807064","https://openalex.org/W2116413942","https://openalex.org/W2118099552","https://openalex.org/W2119187866","https://openalex.org/W2130903752","https://openalex.org/W2131479143","https://openalex.org/W2131628350","https://openalex.org/W2132345820","https://openalex.org/W2133491790","https://openalex.org/W2135046866","https://openalex.org/W2135562430","https://openalex.org/W2135624048","https://openalex.org/W2136979193","https://openalex.org/W2144752499","https://openalex.org/W2145620688","https://openalex.org/W2145962650","https://openalex.org/W2148522164","https://openalex.org/W2151103935","https://openalex.org/W2153635508","https://openalex.org/W2159514083","https://openalex.org/W2162854380","https://openalex.org/W2162979438","https://openalex.org/W2163482144","https://openalex.org/W2166721725","https://openalex.org/W2296319761","https://openalex.org/W2435251607","https://openalex.org/W2604653582","https://openalex.org/W2625093932","https://openalex.org/W2798909945","https://openalex.org/W2912522929","https://openalex.org/W2913340405","https://openalex.org/W2949664970","https://openalex.org/W2994340921","https://openalex.org/W3009608574","https://openalex.org/W3010453621","https://openalex.org/W4246745453","https://openalex.org/W4250589301","https://openalex.org/W4285719527","https://openalex.org/W4394641052","https://openalex.org/W6600062020","https://openalex.org/W6750230808","https://openalex.org/W6750968397"],"related_works":["https://openalex.org/W4214812386","https://openalex.org/W2963086517","https://openalex.org/W2564735875","https://openalex.org/W2378916131","https://openalex.org/W3123504125","https://openalex.org/W3147739796","https://openalex.org/W4224903686","https://openalex.org/W4387770141","https://openalex.org/W2886463271","https://openalex.org/W2916621068"],"abstract_inverted_index":{"We":[0,65,97,150],"consider":[1],"the":[2,26,69,83,86,92,99,103,108,112,129,169,172,178,184,198,201,207,210],"problem":[3,135],"of":[4,111,118,161,171,193,200,209],"learning":[5,22,181,204],"incoherent":[6],"sparse":[7,27],"and":[8,28,38,91,106,145,157,206],"low-rank":[9,29,40],"patterns":[10,30],"from":[11],"multiple":[12],"tasks.":[13],"Our":[14],"approach":[15],"is":[16,45,89,95],"based":[17],"on":[18,190],"a":[19,34,39,78,122,134,191],"linear":[20],"multi-task":[21,180,203],"formulation,":[23,85],"in":[24,82,163],"which":[25,54],"are":[31],"induced":[32],"by":[33],"cardinality":[35],"regularization":[36],"term":[37],"constraint,":[41],"respectively.":[42],"This":[43],"formulation":[44,182,205],"non-convex;":[46],"we":[47,126,167],"convert":[48],"it":[49],"into":[50],"its":[51],"convex":[52,79],"surrogate,":[53],"can":[55,136],"be":[56,137],"routinely":[57],"solved":[58],"via":[59,139],"semidefinite":[60],"programming":[61],"for":[62,101,177],"small-size":[63],"problems.":[64],"propose":[66],"to":[67,74,132],"employ":[68],"general":[70],"projected":[71,104,113,119,154,174,212],"gradient":[72,105,114,120,155,175,213],"scheme":[73],"efficiently":[75],"solve":[76],"such":[77,133],"surrogate;":[80],"however,":[81],"optimization":[84,124,143],"objective":[87],"function":[88],"non-differentiable":[90],"feasible":[93],"domain":[94],"non-trivial.":[96],"present":[98,152],"procedures":[100],"computing":[102],"ensuring":[107],"global":[109],"convergence":[110,162],"scheme.":[115],"The":[116],"computation":[117],"involves":[121],"constrained":[123],"problem;":[125],"show":[127],"that":[128],"optimal":[130],"solution":[131],"obtained":[138],"solving":[140],"an":[141,146],"unconstrained":[142],"subproblem":[144],"Euclidean":[147],"projection":[148],"subproblem.":[149],"also":[151],"two":[153],"algorithms":[156,176],"analyze":[158],"their":[159],"rates":[160],"details.":[164],"In":[165],"addition,":[166],"illustrate":[168],"use":[170],"presented":[173],"proposed":[179,202,211],"using":[183],"least":[185],"squares":[186],"loss.":[187],"Experimental":[188],"results":[189],"collection":[192],"real-world":[194],"data":[195],"sets":[196],"demonstrate":[197],"effectiveness":[199],"efficiency":[208],"algorithms.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":9}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
