{"id":"https://openalex.org/W1995053025","doi":"https://doi.org/10.1145/1081870.1081900","title":"Robust boosting and its relation to bagging","display_name":"Robust boosting and its relation to bagging","publication_year":2005,"publication_date":"2005-08-21","ids":{"openalex":"https://openalex.org/W1995053025","doi":"https://doi.org/10.1145/1081870.1081900","mag":"1995053025"},"language":"en","primary_location":{"id":"doi:10.1145/1081870.1081900","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1081870.1081900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining","raw_type":"proceedings-article"},"type":"conference-paper","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/A5039021124","display_name":"Saharon Rosset","orcid":"https://orcid.org/0000-0002-4458-9545"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Saharon Rosset","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown Heights, NY","IBM -- T. J. Watson Research Center, Yorktown Heights, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM -- T. J. Watson Research Center, Yorktown Heights, NY","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5039021124"],"corresponding_institution_ids":["https://openalex.org/I4210114115"],"apc_list":null,"apc_paid":null,"fwci":0.9858,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.75821587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"249","last_page":"255"},"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":0.9945999979972839,"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":0.9945999979972839,"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/T10057","display_name":"Face and Expression Recognition","score":0.991599977016449,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9914000034332275,"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/boosting","display_name":"Boosting (machine learning)","score":0.7970373630523682},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6384567022323608},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5246524810791016},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5127385854721069},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4663134515285492},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.46041280031204224},{"id":"https://openalex.org/keywords/weight-function","display_name":"Weight function","score":0.44713351130485535},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.43658357858657837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.38139912486076355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.349756121635437},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.33373308181762695},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29997801780700684},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12456712126731873},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07743450999259949}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7970373630523682},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6384567022323608},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5246524810791016},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5127385854721069},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4663134515285492},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.46041280031204224},{"id":"https://openalex.org/C134466208","wikidata":"https://www.wikidata.org/wiki/Q1520657","display_name":"Weight function","level":2,"score":0.44713351130485535},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.43658357858657837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38139912486076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.349756121635437},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33373308181762695},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29997801780700684},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12456712126731873},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07743450999259949},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1081870.1081900","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1081870.1081900","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.103.4108","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.103.4108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.tau.ac.il/~saharon/papers/bagboost.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.386.8031","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.386.8031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.uiuc.edu/class/fa05/cs591han/kdd05/docs/p249.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W1480376833","https://openalex.org/W1570592793","https://openalex.org/W1678356000","https://openalex.org/W1975846642","https://openalex.org/W1988790447","https://openalex.org/W2024046085","https://openalex.org/W2046033161","https://openalex.org/W2084812512","https://openalex.org/W2108263314","https://openalex.org/W2112076978","https://openalex.org/W2119073761","https://openalex.org/W2121805075","https://openalex.org/W2152761983","https://openalex.org/W2154579312","https://openalex.org/W2168885649","https://openalex.org/W2294105907","https://openalex.org/W2912934387","https://openalex.org/W2976840617","https://openalex.org/W6678208612","https://openalex.org/W6684701998"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"Several":[0],"authors":[1],"have":[2],"suggested":[3],"viewing":[4],"boosting":[5,67],"as":[6,66],"a":[7,12,69,99],"gradient":[8,26],"descent":[9],"search":[10],"for":[11,39,82,102],"good":[13],"fit":[14],"in":[15],"function":[16],"space.":[17],"At":[18,51],"each":[19],"iteration":[20],"observations":[21],"are":[22],"re-weighted":[23],"using":[24],"the":[25,28,47,52,76],"of":[27,36,55,79,93],"underlying":[29,48,71],"loss":[30,49,72,104],"function.":[31,50,73],"We":[32,74],"present":[33,87],"an":[34,88],"approach":[35,58],"weight":[37,80,94],"decay":[38,56,81,95],"observation":[40],"weights":[41],"which":[42,62],"is":[43],"equivalent":[44],"to":[45,60],"\"robustifying\"":[46],"extreme":[53],"end":[54],"this":[57],"converges":[59],"Bagging,":[61],"can":[63],"be":[64],"viewed":[65],"with":[68],"linear":[70],"illustrate":[75],"practical":[77],"usefulness":[78],"improving":[83],"prediction":[84],"performance":[85],"and":[86,96],"equivalence":[89],"between":[90],"one":[91],"form":[92],"\"Huberizing\"":[97],"---":[98],"statistical":[100],"method":[101],"making":[103],"functions":[105],"more":[106],"robust.":[107]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
