{"id":"https://openalex.org/W3203502408","doi":"https://doi.org/10.1080/10618600.2022.2116446","title":"Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization","display_name":"Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization","publication_year":2022,"publication_date":"2022-08-24","ids":{"openalex":"https://openalex.org/W3203502408","doi":"https://doi.org/10.1080/10618600.2022.2116446","mag":"3203502408"},"language":"en","primary_location":{"id":"doi:10.1080/10618600.2022.2116446","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2116446","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Accelerated_Componentwise_Gradient_Boosting_using_Efficient_Data_Representation_and_Momentum-based_Optimization/20604833","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029808621","display_name":"Daniel Schalk","orcid":"https://orcid.org/0000-0003-0950-1947"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]},{"id":"https://openalex.org/I3018771216","display_name":"LMU Klinikum","ror":"https://ror.org/02jet3w32","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Daniel Schalk","raw_affiliation_strings":["Department of Statistics, LMU Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, LMU Munich, Munich, Germany","institution_ids":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069072700","display_name":"Bernd Bischl","orcid":"https://orcid.org/0000-0001-6002-6980"},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]},{"id":"https://openalex.org/I3018771216","display_name":"LMU Klinikum","ror":"https://ror.org/02jet3w32","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernd Bischl","raw_affiliation_strings":["Department of Statistics, LMU Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, LMU Munich, Munich, Germany","institution_ids":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067248213","display_name":"David R\u00fcgamer","orcid":"https://orcid.org/0000-0002-8772-9202"},"institutions":[{"id":"https://openalex.org/I3018771216","display_name":"LMU Klinikum","ror":"https://ror.org/02jet3w32","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]},{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David R\u00fcgamer","raw_affiliation_strings":["Department of Statistics, LMU Munich, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, LMU Munich, Munich, Germany","institution_ids":["https://openalex.org/I3018771216","https://openalex.org/I8204097"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029808621"],"corresponding_institution_ids":["https://openalex.org/I3018771216","https://openalex.org/I8204097"],"apc_list":null,"apc_paid":null,"fwci":0.3979,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64555846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"32","issue":"2","first_page":"631","last_page":"641"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9980999827384949,"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":0.9980999827384949,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9979000091552734,"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":0.9954000115394592,"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/interpretability","display_name":"Interpretability","score":0.8472132682800293},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7319183349609375},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7074968814849854},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.7059850096702576},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6945145726203918},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5641484260559082},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5593255162239075},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5337473154067993},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.49767830967903137},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.48234957456588745},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.4355488717556},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4335235357284546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4061970114707947},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3998050093650818},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35513627529144287},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14765897393226624},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.08788725733757019}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8472132682800293},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7319183349609375},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7074968814849854},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.7059850096702576},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6945145726203918},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5641484260559082},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5593255162239075},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5337473154067993},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.49767830967903137},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.48234957456588745},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.4355488717556},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4335235357284546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4061970114707947},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3998050093650818},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35513627529144287},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14765897393226624},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.08788725733757019},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"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":3,"locations":[{"id":"doi:10.1080/10618600.2022.2116446","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10618600.2022.2116446","pdf_url":null,"source":{"id":"https://openalex.org/S76159266","display_name":"Journal of Computational and Graphical Statistics","issn_l":"1061-8600","issn":["1061-8600","1537-2715"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational and Graphical Statistics","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/20604833","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Accelerated_Componentwise_Gradient_Boosting_using_Efficient_Data_Representation_and_Momentum-based_Optimization/20604833","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"doi:10.6084/m9.figshare.20604833.v2","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.20604833.v2","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20604833","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Accelerated_Componentwise_Gradient_Boosting_using_Efficient_Data_Representation_and_Momentum-based_Optimization/20604833","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321114","display_name":"Bundesministerium f\u00fcr Bildung und Forschung","ror":"https://ror.org/04pz7b180"},{"id":"https://openalex.org/F4320323015","display_name":"Bundesministerium f\u00fcr Forschung und Technologie","ror":"https://ror.org/04pz7b180"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1980287119","https://openalex.org/W1990420052","https://openalex.org/W2017008479","https://openalex.org/W2039380015","https://openalex.org/W2051922388","https://openalex.org/W2083542829","https://openalex.org/W2088883866","https://openalex.org/W2099968818","https://openalex.org/W2112076978","https://openalex.org/W2143339960","https://openalex.org/W2147542748","https://openalex.org/W2155542219","https://openalex.org/W2156858199","https://openalex.org/W2162430620","https://openalex.org/W2295598076","https://openalex.org/W2468874071","https://openalex.org/W2523246573","https://openalex.org/W2582743722","https://openalex.org/W2588369015","https://openalex.org/W2611002985","https://openalex.org/W2843469511","https://openalex.org/W2895807746","https://openalex.org/W2918221993","https://openalex.org/W2936995161","https://openalex.org/W2963416944","https://openalex.org/W2963820355","https://openalex.org/W2973631113","https://openalex.org/W2996370717","https://openalex.org/W2996717911","https://openalex.org/W3004780002","https://openalex.org/W3007093918","https://openalex.org/W3084336747","https://openalex.org/W3102476541","https://openalex.org/W3105439568","https://openalex.org/W3128452405","https://openalex.org/W4239035626","https://openalex.org/W4399648971","https://openalex.org/W6601630192","https://openalex.org/W6753109434","https://openalex.org/W6821924414"],"related_works":["https://openalex.org/W2895097035","https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W3020853991","https://openalex.org/W4362706668","https://openalex.org/W4231621013","https://openalex.org/W3171021120","https://openalex.org/W3008318776"],"abstract_inverted_index":{"Componentwise":[0],"boosting":[1,13],"(CWB),":[2],"also":[3,98,136],"known":[4],"as":[5,19,37],"model-based":[6],"boosting,":[7],"is":[8,26,48],"a":[9,100,105],"variant":[10],"of":[11,46,54,73,77],"gradient":[12,86,108],"that":[14,103],"builds":[15],"on":[16,155],"additive":[17],"models":[18,34],"base":[20],"learners":[21],"to":[22,39,65,94,143,161],"ensure":[23],"interpretability.":[24],"CWB":[25,47,119,138],"thus":[27],"often":[28],"used":[29],"in":[30,42,52,147,165],"research":[31],"areas":[32],"where":[33],"are":[35],"employed":[36],"tools":[38],"explain":[40],"relationships":[41],"data.":[43],"One":[44],"downside":[45],"its":[49],"computational":[50],"complexity":[51],"terms":[53],"memory":[55,122,168],"and":[56,80,124,141,158,167,174],"runtime.":[57],"In":[58],"this":[59],"article,":[60],"we":[61,97],"propose":[62,99],"two":[63],"techniques":[64],"overcome":[66],"these":[67],"issues":[68],"without":[69],"losing":[70],"the":[71,89,127,163],"properties":[72],"CWB:":[74],"feature":[75,133],"discretization":[76],"numerical":[78],"features":[79],"incorporating":[81],"Nesterov":[82],"momentum":[83],"into":[84],"functional":[85],"descent.":[87],"As":[88],"latter":[90],"can":[91],"be":[92],"prone":[93],"early":[95],"overfitting,":[96],"hybrid":[101],"approach":[102],"prevents":[104],"possibly":[106],"diverging":[107],"descent":[109],"routine":[110],"while":[111,135,170],"ensuring":[112],"faster":[113,140],"convergence.":[114],"Our":[115],"adaptions":[116],"improve":[117],"vanilla":[118],"by":[120],"reducing":[121],"consumption":[123,169],"speeding":[125],"up":[126],"computation":[128],"time":[129],"per":[130],"iteration":[131],"(through":[132],"discretization)":[134],"enabling":[137],"learn":[139],"hence":[142],"require":[144],"fewer":[145],"iterations":[146],"total":[148],"using":[149],"momentum.":[150],"We":[151],"perform":[152],"extensive":[153],"benchmarks":[154],"multiple":[156],"simulated":[157],"real-world":[159],"datasets":[160],"demonstrate":[162],"improvements":[164],"runtime":[166],"maintaining":[171],"state-of-the-art":[172],"estimation":[173],"prediction":[175],"performance.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}