{"id":"https://openalex.org/W2946273655","doi":"https://doi.org/10.1109/tkde.2019.2916683","title":"Improving Data Analytics with Fast and Adaptive Regularization","display_name":"Improving Data Analytics with Fast and Adaptive Regularization","publication_year":2019,"publication_date":"2019-05-13","ids":{"openalex":"https://openalex.org/W2946273655","doi":"https://doi.org/10.1109/tkde.2019.2916683","mag":"2946273655"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2019.2916683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2019.2916683","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5027609768","display_name":"Zhaojing Luo","orcid":"https://orcid.org/0000-0001-7271-3999"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Zhaojing Luo","raw_affiliation_strings":["Schoool of Computing, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Schoool of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001683040","display_name":"Shaofeng Cai","orcid":"https://orcid.org/0000-0001-8605-076X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shaofeng Cai","raw_affiliation_strings":["Schoool of Computing, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Schoool of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389286","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-7483-0045"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000935850","display_name":"Jinyang Gao","orcid":"https://orcid.org/0000-0001-8247-1196"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jinyang Gao","raw_affiliation_strings":["Schoool of Computing, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Schoool of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091716232","display_name":"Wang-Chien Lee","orcid":"https://orcid.org/0000-0002-8949-489X"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wang-Chien Lee","raw_affiliation_strings":["Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054008198","display_name":"Kee Yuan Ngiam","orcid":"https://orcid.org/0000-0001-5676-2520"},"institutions":[{"id":"https://openalex.org/I4210150261","display_name":"National University Health System","ror":"https://ror.org/05tjjsh18","country_code":"SG","type":"education","lineage":["https://openalex.org/I4210150261"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kee Yuan Ngiam","raw_affiliation_strings":["National University Health System, Singapore"],"affiliations":[{"raw_affiliation_string":"National University Health System, Singapore","institution_ids":["https://openalex.org/I4210150261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032263010","display_name":"Meihui Zhang","orcid":"https://orcid.org/0000-0002-0752-9877"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meihui Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5027609768"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.7235,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.7819128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"33","issue":"2","first_page":"551","last_page":"568"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9976999759674072,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9976999759674072,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973999857902527,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.996399998664856,"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":0.7793819904327393},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7549827098846436},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.702366828918457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5393175482749939},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5049377083778381},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49674731492996216},{"id":"https://openalex.org/keywords/regularization-perspectives-on-support-vector-machines","display_name":"Regularization perspectives on support vector machines","score":0.41965562105178833},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4144229292869568},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3523140847682953},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1793220043182373},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.1468084454536438},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12855961918830872}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7793819904327393},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7549827098846436},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.702366828918457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393175482749939},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5049377083778381},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49674731492996216},{"id":"https://openalex.org/C141718189","wikidata":"https://www.wikidata.org/wiki/Q7309628","display_name":"Regularization perspectives on support vector machines","level":4,"score":0.41965562105178833},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4144229292869568},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3523140847682953},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1793220043182373},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.1468084454536438},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12855961918830872},{"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/C152442038","wikidata":"https://www.wikidata.org/wiki/Q2778212","display_name":"Tikhonov regularization","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2019.2916683","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2019.2916683","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1588402114","display_name":null,"funder_award_id":"IIS-1717084","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309374","display_name":"Ohio State University","ror":"https://ror.org/00rs6vg23"},{"id":"https://openalex.org/F4320310419","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231"},{"id":"https://openalex.org/F4320322927","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884"},{"id":"https://openalex.org/F4320324787","display_name":"Peking University","ror":"https://ror.org/02v51f717"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1202352811","https://openalex.org/W1480376833","https://openalex.org/W1533803232","https://openalex.org/W1597017619","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1701825639","https://openalex.org/W1849277567","https://openalex.org/W1862694079","https://openalex.org/W1934084512","https://openalex.org/W1997453445","https://openalex.org/W2010824638","https://openalex.org/W2011873184","https://openalex.org/W2013640190","https://openalex.org/W2062022900","https://openalex.org/W2097998348","https://openalex.org/W2099102906","https://openalex.org/W2106411961","https://openalex.org/W2113145584","https://openalex.org/W2117539524","https://openalex.org/W2121990650","https://openalex.org/W2122825543","https://openalex.org/W2131241448","https://openalex.org/W2135046866","https://openalex.org/W2144513243","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2231162939","https://openalex.org/W2251084241","https://openalex.org/W2407212869","https://openalex.org/W2509427142","https://openalex.org/W2509532045","https://openalex.org/W2525739395","https://openalex.org/W2552875608","https://openalex.org/W2605357614","https://openalex.org/W2728797307","https://openalex.org/W2745238137","https://openalex.org/W2752236330","https://openalex.org/W2794455536","https://openalex.org/W2803210060","https://openalex.org/W2962677560","https://openalex.org/W2962687950","https://openalex.org/W2962737134","https://openalex.org/W2962746093","https://openalex.org/W2962835968","https://openalex.org/W2964058534","https://openalex.org/W2964073168","https://openalex.org/W3098834468","https://openalex.org/W3118608800","https://openalex.org/W3120740533","https://openalex.org/W6631818155","https://openalex.org/W6637373629","https://openalex.org/W6637653338","https://openalex.org/W6674385629","https://openalex.org/W6676179485","https://openalex.org/W6676544178","https://openalex.org/W6678911119","https://openalex.org/W6681151457","https://openalex.org/W6684191040","https://openalex.org/W6705002163","https://openalex.org/W6725272734","https://openalex.org/W6740824378","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W3099765033","https://openalex.org/W2366023887","https://openalex.org/W1989857057","https://openalex.org/W3110578843","https://openalex.org/W2388364587","https://openalex.org/W2062975788","https://openalex.org/W1570628932","https://openalex.org/W4254199101","https://openalex.org/W2935233291","https://openalex.org/W2783547182"],"abstract_inverted_index":{"Deep":[0],"Learning":[1,4],"and":[2,36,153,164,174,194],"Machine":[3],"models":[5,20,41],"have":[6,28],"recently":[7],"been":[8],"shown":[9],"to":[10,47,56,78,119,126,157],"be":[11],"effective":[12,134],"in":[13,54,60],"many":[14],"real":[15],"world":[16],"applications.":[17],"While":[18],"these":[19],"achieve":[21],"increasingly":[22],"better":[23],"predictive":[24],"performance,":[25],"their":[26],"structures":[27],"also":[29],"become":[30],"much":[31],"more":[32],"complex.":[33],"A":[34],"common":[35],"difficult":[37,77],"problem":[38],"for":[39],"complex":[40],"is":[42,45,66,76,171],"overfitting.":[43,58],"Regularization":[44],"used":[46],"penalize":[48],"the":[49,52,73,103,121,127,159,178],"complexity":[50],"of":[51,91,180,197],"model":[53],"order":[55],"avoid":[57],"However,":[59],"most":[61],"learning":[62,200],"frameworks,":[63],"regularization":[64,87,112,123,169,182,209,216],"function":[65,124],"usually":[67],"set":[68],"with":[69,142],"some":[70],"hyper-parameters":[71],"where":[72],"best":[74,122],"setting":[75],"find.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83,107,131,148],"propose":[84,108],"an":[85,133,185],"adaptive":[86,111,208],"method,":[88],"as":[89],"part":[90],"a":[92,109,150],"large":[93],"end-to-end":[94],"healthcare":[95],"data":[96],"analytics":[97],"software":[98],"stack,":[99],"which":[100,137],"effectively":[101],"addresses":[102],"above":[104],"difficulty.":[105],"First,":[106],"general":[110],"method":[113,183,210],"based":[114],"on":[115],"Gaussian":[116],"Mixture":[117],"(GM)":[118],"learn":[120],"according":[125],"observed":[128],"parameters.":[129],"Second,":[130],"develop":[132],"update":[135,152,155],"algorithm":[136,156],"integrates":[138],"Expectation":[139],"Maximization":[140],"(EM)":[141],"Stochastic":[143],"Gradient":[144],"Descent":[145],"(SGD).":[146],"Third,":[147],"design":[149],"lazy":[151],"sparse":[154],"reduce":[158],"computational":[160],"cost":[161],"by":[162],"4x":[163],"20x,":[165],"respectively.":[166],"The":[167,202],"overall":[168],"framework":[170],"fast,":[172],"adaptive,":[173],"easy-to-use.":[175],"We":[176],"validate":[177],"effectiveness":[179],"our":[181,206],"through":[184],"extensive":[186],"experimental":[187],"study":[188],"over":[189,214],"14":[190],"standard":[191],"benchmark":[192],"datasets":[193],"three":[195],"kinds":[196],"deep":[198],"learning/machine":[199],"models.":[201],"results":[203],"illustrate":[204],"that":[205],"proposed":[207],"achieves":[211],"significant":[212],"improvement":[213],"state-of-the-art":[215],"methods.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}