{"id":"https://openalex.org/W2996124338","doi":"https://doi.org/10.1145/3362077.3362085","title":"Advancing non-convex and constrained learning","display_name":"Advancing non-convex and constrained learning","publication_year":2019,"publication_date":"2019-12-06","ids":{"openalex":"https://openalex.org/W2996124338","doi":"https://doi.org/10.1145/3362077.3362085","mag":"2996124338"},"language":"en","primary_location":{"id":"doi:10.1145/3362077.3362085","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3362077.3362085","pdf_url":null,"source":{"id":"https://openalex.org/S4210187303","display_name":"AI Matters","issn_l":"2372-3483","issn":["2372-3483"],"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":"AI Matters","raw_type":"journal-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/A5023288846","display_name":"Tianbao Yang","orcid":"https://orcid.org/0000-0002-7858-5438"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianbao Yang","raw_affiliation_strings":["The University of Iowa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5023288846"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":1.596,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88161506,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"5","issue":"3","first_page":"29","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9988999962806702,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9988999962806702,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9979000091552734,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9962999820709229,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6131598353385925},{"id":"https://openalex.org/keywords/zh\u00e0ng","display_name":"Zh\u00e0ng","score":0.52665114402771},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.5140053033828735},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.506170928478241},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46250292658805847},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4433504641056061},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4183392822742462},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37030500173568726},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3535288870334625},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.108740895986557},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.06143108010292053}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6131598353385925},{"id":"https://openalex.org/C2777045944","wikidata":"https://www.wikidata.org/wiki/Q12170198","display_name":"Zh\u00e0ng","level":3,"score":0.52665114402771},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.5140053033828735},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.506170928478241},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46250292658805847},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4433504641056061},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4183392822742462},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37030500173568726},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3535288870334625},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.108740895986557},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.06143108010292053},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3362077.3362085","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3362077.3362085","pdf_url":null,"source":{"id":"https://openalex.org/S4210187303","display_name":"AI Matters","issn_l":"2372-3483","issn":["2372-3483"],"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":"AI Matters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":90,"referenced_works":["https://openalex.org/W1569098853","https://openalex.org/W1849979240","https://openalex.org/W1965125844","https://openalex.org/W1967138577","https://openalex.org/W1994974865","https://openalex.org/W2009941369","https://openalex.org/W2027982384","https://openalex.org/W2031993275","https://openalex.org/W2050724550","https://openalex.org/W2061598070","https://openalex.org/W2069010445","https://openalex.org/W2074682976","https://openalex.org/W2079705627","https://openalex.org/W2089394015","https://openalex.org/W2099471712","https://openalex.org/W2102026903","https://openalex.org/W2107861471","https://openalex.org/W2114296159","https://openalex.org/W2116626343","https://openalex.org/W2156005216","https://openalex.org/W2170262790","https://openalex.org/W2173520492","https://openalex.org/W2184634347","https://openalex.org/W2194775991","https://openalex.org/W2248060815","https://openalex.org/W2288624927","https://openalex.org/W2343766162","https://openalex.org/W2530395818","https://openalex.org/W2540757487","https://openalex.org/W2546420264","https://openalex.org/W2564590721","https://openalex.org/W2594166818","https://openalex.org/W2609037894","https://openalex.org/W2626224734","https://openalex.org/W2626982520","https://openalex.org/W2739748921","https://openalex.org/W2740178347","https://openalex.org/W2741924441","https://openalex.org/W2747280560","https://openalex.org/W2747329762","https://openalex.org/W2750786826","https://openalex.org/W2758197809","https://openalex.org/W2765599067","https://openalex.org/W2771029897","https://openalex.org/W2786313301","https://openalex.org/W2796892552","https://openalex.org/W2808042107","https://openalex.org/W2808402975","https://openalex.org/W2886067286","https://openalex.org/W2886697509","https://openalex.org/W2891952073","https://openalex.org/W2894604724","https://openalex.org/W2895628298","https://openalex.org/W2899748887","https://openalex.org/W2900959181","https://openalex.org/W2913059114","https://openalex.org/W2919115771","https://openalex.org/W2922131323","https://openalex.org/W2944407464","https://openalex.org/W2949935872","https://openalex.org/W2950597526","https://openalex.org/W2951773851","https://openalex.org/W2953148557","https://openalex.org/W2962717811","https://openalex.org/W2962723573","https://openalex.org/W2962939792","https://openalex.org/W2963075511","https://openalex.org/W2963084730","https://openalex.org/W2963327228","https://openalex.org/W2963349772","https://openalex.org/W2963373709","https://openalex.org/W2963470657","https://openalex.org/W2963625269","https://openalex.org/W2963857521","https://openalex.org/W2963981733","https://openalex.org/W2964126461","https://openalex.org/W2964232258","https://openalex.org/W2964294232","https://openalex.org/W2964334726","https://openalex.org/W2964772384","https://openalex.org/W2965658867","https://openalex.org/W2966596327","https://openalex.org/W2998508934","https://openalex.org/W3003284525","https://openalex.org/W3004560401","https://openalex.org/W3098306969","https://openalex.org/W3103245321","https://openalex.org/W3122112575","https://openalex.org/W3159754263","https://openalex.org/W4289258088"],"related_works":["https://openalex.org/W2364559953","https://openalex.org/W2375840727","https://openalex.org/W2389678104","https://openalex.org/W2375137083","https://openalex.org/W2380507695","https://openalex.org/W2367687999","https://openalex.org/W2387562377","https://openalex.org/W2384722335","https://openalex.org/W2376544228","https://openalex.org/W2371486229"],"abstract_inverted_index":{"As":[0],"data":[1,128,306],"gets":[2],"more":[3,89,161],"complex":[4],"and":[5,15,53,307],"applications":[6],"of":[7,64,80,283,300,310],"machine":[8],"learning":[9,47,52,65,81,118,123,168,190,290],"(ML)":[10],"algorithms":[11,303],"for":[12,122,154,167,304],"decision-making":[13],"broaden":[14],"diversify,":[16],"traditional":[17],"ML":[18,39],"methods":[19,66,82],"by":[20,287],"minimizing":[21],"an":[22],"unconstrained":[23],"or":[24,157],"simply":[25],"constrained":[26,55,189],"convex":[27,165],"objective":[28],"are":[29,87],"becoming":[30],"increasingly":[31],"unsatisfactory.":[32],"To":[33],"address":[34],"this":[35],"new":[36,289],"challenge,":[37],"recent":[38],"research":[40],"has":[41,109,119],"sparked":[42],"a":[43,62,78,92],"paradigm":[44,107],"shift":[45,108],"in":[46,103],"predictive":[48,196],"models":[49,171,197],"into":[50],"non-convex":[51,70,100,116,151],"heavily":[54],"learning.":[56,105],"Non-Convex":[57],"Learning":[58,74],"(NCL)":[59],"refers":[60,76],"to":[61,77,194,202,237,259,297],"family":[63,79],"that":[67,83,86,198],"involve":[68,84],"optimizing":[69],"objectives.":[71],"Heavily":[72],"Constrained":[73],"(HCL)":[75],"constraints":[85,201],"much":[88],"complicated":[90],"than":[91,163],"simple":[93],"norm":[94],"constraint":[95],"(e.g.,":[96,129,153,206],"data-dependent":[97],"functional":[98],"constraints,":[99],"constraints),":[101],"as":[102],"conventional":[104],"This":[106],"already":[110],"created":[111],"many":[112],"promising":[113],"outcomes:":[114],"(i)":[115],"deep":[117],"brought":[120,286],"breakthroughs":[121],"representations":[124],"from":[125],"large-scale":[126],"structured":[127,170],"images,":[130],"speech)":[131],"(LeCun,":[132],"Bengio,":[133],"&":[134,139,147,174,179,213,226,234,249,256,264,269,277],"Hinton,":[135,140],"2015;":[136],"Krizhevsky,":[137],"Sutskever,":[138],"2012;":[141,176],"Amodei":[142],"et":[143,219,242],"al.,":[144,220,243],"2016;":[145,221,244,251],"Deng":[146],"Liu,":[148],"2018);":[149],"(ii)":[150],"regularizers":[152],"enforcing":[155],"sparsity":[156],"low-rank)":[158],"could":[159],"be":[160],"effective":[162],"their":[164,311],"counterparts":[166],"high-dimensional":[169],"(C.-H.":[172],"Zhang":[173],"Zhang,":[175,183,186,276],"J.":[177],"Fan":[178],"Li,":[180],"2001;":[181],"C.-H.":[182],"2010;":[184],"T.":[185,272],"2010);":[187],"(iii)":[188],"is":[191],"being":[192],"used":[193],"learn":[195],"satisfy":[199],"various":[200],"respect":[203],"social":[204],"norms":[205],"fairness)":[207],"(B.":[208],"E.":[209],"Woodworth,":[210],"Gunasekar,":[211],"Ohannessian,":[212],"Srebro,":[214,218],"2017;":[215,228],"Hardt,":[216],"Price,":[217],"Zafar,":[222],"Valera,":[223],"Gomez":[224],"Rodriguez,":[225],"Gummadi,":[227],"A.":[229],"Agarwal,":[230],"Beygelzimer,":[231],"Dud\u00edk,":[232],"Langford,":[233],"Wallach,":[235],"2018),":[236],"improve":[238],"the":[239,261,298,308],"interpretability":[240],"(Gupta":[241],"Canini,":[245,254],"Cotter,":[246],"Gupta,":[247,257],"Fard,":[248],"Pfeifer,":[250,255],"You,":[252],"Ding,":[253],"2017),":[258],"enhance":[260],"robustness":[262],"(Globerson":[263],"Roweis,":[265],"2006a;":[266],"Sra,":[267],"Nowozin,":[268],"Wright,":[270],"2011;":[271],"Yang,":[273],"Mahdavi,":[274],"Jin,":[275],"Zhou,":[278],"2012),":[279],"etc.":[280],"In":[281],"spite":[282],"great":[284],"promises":[285],"these":[288],"paradigms,":[291],"they":[292],"also":[293],"bring":[294],"emerging":[295],"challenges":[296],"design":[299],"computationally":[301],"efficient":[302],"big":[305],"analysis":[309],"statistical":[312],"properties.":[313]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":6}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}