{"id":"https://openalex.org/W2965792187","doi":"https://doi.org/10.24963/ijcai.2019/332","title":"Sketched Iterative Algorithms for Structured Generalized Linear Models","display_name":"Sketched Iterative Algorithms for Structured Generalized Linear Models","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2965792187","doi":"https://doi.org/10.24963/ijcai.2019/332","mag":"2965792187"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/332","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/332","pdf_url":"https://www.ijcai.org/proceedings/2019/0332.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0332.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101811743","display_name":"Qilong Gu","orcid":"https://orcid.org/0000-0002-0794-8211"},"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":"Qilong Gu","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities","Department of Computer Science & Engineering, University of Minnesota, Twin-Cities"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin-Cities","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"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":true,"raw_author_name":"Arindam Banerjee","raw_affiliation_strings":["Department of Computer Science & Engineering, University of Minnesota, Twin Cities","Department of Computer Science & Engineering, University of Minnesota, Twin-Cities"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin Cities","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]},{"raw_affiliation_string":"Department of Computer Science & Engineering, University of Minnesota, Twin-Cities","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014459472"],"corresponding_institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08621848,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2392","last_page":"2398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9998000264167786,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.7749261856079102},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6627039313316345},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6405126452445984},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6174984574317932},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.559734046459198},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4921419024467468},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.46665096282958984},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.44422969222068787},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.4398859739303589},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41706350445747375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30922454595565796},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25199735164642334},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18681243062019348}],"concepts":[{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.7749261856079102},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6627039313316345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6405126452445984},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6174984574317932},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.559734046459198},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4921419024467468},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.46665096282958984},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.44422969222068787},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.4398859739303589},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41706350445747375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30922454595565796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25199735164642334},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18681243062019348},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/332","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/332","pdf_url":"https://www.ijcai.org/proceedings/2019/0332.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/332","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/332","pdf_url":"https://www.ijcai.org/proceedings/2019/0332.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1211320294","display_name":null,"funder_award_id":"IIS-1029711","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1377627663","display_name":"BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data","funder_award_id":"1447566","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1648129465","display_name":null,"funder_award_id":"CNS-1314560","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G208115193","display_name":"TWC: Medium: Collaborative: HIMALAYAS: Hierarchical Machine Learning Stack for Fine-Grained Analysis of Malware Domain Groups","funder_award_id":"1314560","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2501928946","display_name":null,"funder_award_id":"IIS-1029711","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G2692851364","display_name":null,"funder_award_id":"IIS-0953274","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G2781174226","display_name":null,"funder_award_id":"IIS-1563950","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4319621678","display_name":"BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data","funder_award_id":"1447574","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4753362727","display_name":"THE CENTRAL OBJECTIVE OF THE PROPOSED PROJECT IS TO DEVELOP ACCURATE, ROBUST, AND SCALABLE METHODS FOR DETECTING PRECURSORS TO AVIATION SAFETY INCIDE","funder_award_id":"NNX12AQ39A","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G5521036603","display_name":"III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions","funder_award_id":"1563950","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G590079505","display_name":"RI: Small: Finding Patterns in Complex Data with Probablistic Graphical Models","funder_award_id":"1422557","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6073761981","display_name":null,"funder_award_id":"CCF-1451986","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G6139495888","display_name":null,"funder_award_id":"IIS-0953274","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7227591233","display_name":null,"funder_award_id":"IIS-1447566","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G7544741629","display_name":null,"funder_award_id":"IIS-1447566","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8022001571","display_name":"Collaborative Research:  Understanding Climate Change: A Data Driven Approach","funder_award_id":"1029711","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8025912458","display_name":null,"funder_award_id":"IIS-1422557","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"},{"id":"https://openalex.org/G8236381349","display_name":null,"funder_award_id":"IIS-1447574","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8532230576","display_name":"CAREER: Combinatorial Online Learning and its Applications","funder_award_id":"0953274","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G947792794","display_name":"EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends","funder_award_id":"1451986","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/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965792187.pdf","grobid_xml":"https://content.openalex.org/works/W2965792187.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1501884374","https://openalex.org/W1791038712","https://openalex.org/W2042465463","https://openalex.org/W2107438106","https://openalex.org/W2118550318","https://openalex.org/W2118901394","https://openalex.org/W2119122547","https://openalex.org/W2121640703","https://openalex.org/W2124659530","https://openalex.org/W2135046866","https://openalex.org/W2152326788","https://openalex.org/W2157988812","https://openalex.org/W2162312215","https://openalex.org/W2365692793","https://openalex.org/W2524385150","https://openalex.org/W2566240941","https://openalex.org/W2570919384","https://openalex.org/W2773306503","https://openalex.org/W2950190315","https://openalex.org/W2952215077","https://openalex.org/W2963002486","https://openalex.org/W2963060476","https://openalex.org/W2963459305","https://openalex.org/W2964309963","https://openalex.org/W3124617746","https://openalex.org/W4230985103","https://openalex.org/W4237284205","https://openalex.org/W4246747007","https://openalex.org/W4294309195"],"related_works":["https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668","https://openalex.org/W2900667084","https://openalex.org/W3008318776","https://openalex.org/W1977633006","https://openalex.org/W2041416246"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2,19,79],"seen":[3],"advances":[4],"in":[5,55],"optimizing":[6],"large":[7],"scale":[8],"statistical":[9,13,84,123],"estimation":[10],"problems.":[11],"In":[12,47],"learning":[14],"settings":[15],"iterative":[16,53,111],"optimization":[17],"algorithms":[18,112],"been":[20],"shown":[21],"to":[22,78,82,95,106,118],"enjoy":[23],"geometric":[24,80],"convergence.":[25],"While":[26],"powerful,":[27],"such":[28],"results":[29],"only":[30],"hold":[31],"for":[32,67],"the":[33,42,83,90,100,120],"original":[34],"dataset,":[35],"and":[36,61,72,125],"may":[37],"face":[38],"computational":[39],"challenges":[40],"when":[41],"sample":[43],"size":[44],"is":[45,93],"large.":[46],"this":[48],"paper,":[49],"we":[50],"study":[51,119],"sketched":[52,110],"algorithms,":[54],"particular":[56],"sketched-PGD":[57],"(projected":[58],"gradient":[59],"descent)":[60],"sketched-SVRG":[62],"(stochastic":[63],"variance":[64],"reduced":[65],"gradient)":[66],"structured":[68],"generalized":[69],"linear":[70],"model,":[71],"illustrate":[73],"that":[74],"these":[75],"methods":[76],"continue":[77],"convergence":[81],"error":[85],"under":[86],"suitable":[87],"assumptions.":[88],"Moreover,":[89],"sketching":[91],"dimension":[92,117],"allowed":[94],"be":[96],"even":[97],"smaller":[98],"than":[99],"ambient":[101],"dimension,":[102],"thus":[103],"can":[104],"lead":[105],"significant":[107],"speed-ups.":[108],"The":[109],"introduced":[113],"provide":[114],"an":[115],"additional":[116],"trade-offs":[121],"between":[122],"accuracy":[124],"time.":[126]},"counts_by_year":[],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}