{"id":"https://openalex.org/W4386242480","doi":"https://doi.org/10.1145/3600211.3604706","title":"REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values","display_name":"REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values","publication_year":2023,"publication_date":"2023-08-08","ids":{"openalex":"https://openalex.org/W4386242480","doi":"https://doi.org/10.1145/3600211.3604706"},"language":"en","primary_location":{"id":"doi:10.1145/3600211.3604706","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3600211.3604706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2403.08880","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101429395","display_name":"Shubham Sharma","orcid":"https://orcid.org/0000-0003-0763-6223"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shubham Sharma","raw_affiliation_strings":["JPMorgan Chase & Co., USA"],"affiliations":[{"raw_affiliation_string":"JPMorgan Chase & Co., USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035222388","display_name":"Sanghamitra Dutta","orcid":"https://orcid.org/0000-0002-6500-2627"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanghamitra Dutta","raw_affiliation_strings":["University of Maryland, College Park, USA"],"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, USA","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007110035","display_name":"Emanuele Albini","orcid":"https://orcid.org/0000-0003-2964-4638"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emanuele Albini","raw_affiliation_strings":["JPMorgan Chase & Co., USA"],"affiliations":[{"raw_affiliation_string":"JPMorgan Chase & Co., USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002426346","display_name":"Freddy L\u00e9cu\u00e9","orcid":"https://orcid.org/0000-0003-2763-7856"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Freddy Lecue","raw_affiliation_strings":["JPMorgan Chase & Co., USA"],"affiliations":[{"raw_affiliation_string":"JPMorgan Chase & Co., USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055757002","display_name":"Daniele Magazzeni","orcid":"https://orcid.org/0000-0002-1934-3447"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniele Magazzeni","raw_affiliation_strings":["JPMorgan Chase & Co., USA"],"affiliations":[{"raw_affiliation_string":"JPMorgan Chase & Co., USA","institution_ids":["https://openalex.org/I1305429384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088276691","display_name":"Manuela Veloso","orcid":"https://orcid.org/0000-0001-6738-238X"},"institutions":[{"id":"https://openalex.org/I1305429384","display_name":"JPMorgan Chase & Co (United States)","ror":"https://ror.org/01x3kkr08","country_code":"US","type":"company","lineage":["https://openalex.org/I1305429384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manuela Veloso","raw_affiliation_strings":["JPMorgan Chase & Co., USA"],"affiliations":[{"raw_affiliation_string":"JPMorgan Chase & Co., USA","institution_ids":["https://openalex.org/I1305429384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101429395"],"corresponding_institution_ids":["https://openalex.org/I1305429384"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1058816,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"443","last_page":"453"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9991000294685364,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9932000041007996,"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":0.7872181534767151},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7737812995910645},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7256730794906616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5428017377853394},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5172175168991089},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5065580606460571},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4855344295501709},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4530661702156067},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4183949828147888}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7872181534767151},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7737812995910645},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7256730794906616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5428017377853394},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5172175168991089},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5065580606460571},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4855344295501709},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4530661702156067},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4183949828147888},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3600211.3604706","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3600211.3604706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2403.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.08880","pdf_url":"https://arxiv.org/pdf/2403.08880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2403.08880","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2403.08880","pdf_url":"https://arxiv.org/pdf/2403.08880","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386242480.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1995806857","https://openalex.org/W2131681506","https://openalex.org/W2506743715","https://openalex.org/W2765146466","https://openalex.org/W2787955716","https://openalex.org/W2888487581","https://openalex.org/W2973941913","https://openalex.org/W2974817986","https://openalex.org/W2988585267","https://openalex.org/W3013149459","https://openalex.org/W3094194083","https://openalex.org/W3099768174","https://openalex.org/W3109369928","https://openalex.org/W3146613606","https://openalex.org/W3163411042","https://openalex.org/W3184621883","https://openalex.org/W3192262438","https://openalex.org/W3193660276","https://openalex.org/W3206048862","https://openalex.org/W3211490561","https://openalex.org/W4282574503","https://openalex.org/W4316038168"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W4281727072","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2377538627","https://openalex.org/W2107220315","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Feature":[0],"selection":[1,73,86,105,137],"is":[2,13,74,183],"a":[3,135,145,155,184,200,214],"crucial":[4],"step":[5],"in":[6],"building":[7],"machine":[8],"learning":[9],"models.":[10,179,207],"This":[11],"process":[12,106,138],"often":[14],"achieved":[15,172],"with":[16,67,76,87,125,142,227],"accuracy":[17],"as":[18,37,96],"an":[19],"objective,":[20],"and":[21,25,39,94,190,239],"can":[22,122,170,194,222],"be":[23,61,123,171],"cumbersome":[24],"computationally":[26,103],"expensive":[27,104],"for":[28,44,53,63,196,237],"large-scale":[29,215],"datasets.":[30],"Several":[31],"additional":[32,162],"model":[33,45,64,80,89,129,168,201,229],"performance":[34,81,90,130,169],"characteristics":[35,65,91,131,230],"such":[36],"fairness":[38,93],"robustness":[40],"are":[41,49,165],"of":[42,116,199],"importance":[43],"development.":[46],"As":[47],"regulations":[48],"driving":[50],"the":[51,102,114,197,235],"need":[52,59,236],"more":[54],"trustworthy":[55],"models,":[56],"deployed":[57],"models":[58,226],"to":[60,78,127,144,157,175,204],"corrected":[62],"associated":[66],"responsible":[68],"artificial":[69],"intelligence.":[70],"When":[71],"feature":[72,85,117,136],"done":[75,141],"respect":[77,126,143],"one":[79],"characteristic":[82],"(eg.":[83,92],"accuracy),":[84],"secondary":[88,128],"robustness)":[95],"objectives":[97],"would":[98],"require":[99],"going":[100],"through":[101],"from":[107],"scratch.":[108],"In":[109],"this":[110,150],"paper,":[111],"we":[112,152],"introduce":[113],"problem":[115],"reselection,":[118],"so":[119,160],"that":[120,161,164,193,220],"features":[121,159],"selected":[124],"efficiently":[132],"even":[133],"after":[134],"has":[139],"been":[140],"primary":[146],"objective.":[147],"To":[148],"address":[149],"problem,":[151],"propose":[153],"REFRESH,":[154],"method":[156],"reselect":[158],"constraints":[163],"desirable":[166],"towards":[167],"without":[173,202],"having":[174,203],"train":[176,205],"several":[177],"new":[178],"REFRESH\u2019s":[180],"underlying":[181],"algorithm":[182],"novel":[185],"technique":[186],"using":[187],"SHAP":[188],"values":[189],"correlation":[191],"analysis":[192],"approximate":[195],"predictions":[198],"these":[206],"Empirical":[208],"evaluations":[209],"on":[210,242],"three":[211],"datasets,":[212],"including":[213],"loan":[216],"defaulting":[217],"dataset":[218],"show":[219],"REFRESH":[221,240],"help":[223],"find":[224],"alternate":[225],"better":[228],"efficiently.":[231],"We":[232],"also":[233],"discuss":[234],"reselection":[238],"based":[241],"regulation":[243],"desiderata.":[244]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}