{"id":"https://openalex.org/W4410356880","doi":"https://doi.org/10.1145/3672608.3707978","title":"D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles","display_name":"D-semble: Efficient Diversity-Guided Search for Resilient ML Ensembles","publication_year":2025,"publication_date":"2025-03-31","ids":{"openalex":"https://openalex.org/W4410356880","doi":"https://doi.org/10.1145/3672608.3707978"},"language":"en","primary_location":{"id":"doi:10.1145/3672608.3707978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3672608.3707978","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3672608.3707978","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091644091","display_name":"Abraham Chan","orcid":"https://orcid.org/0000-0002-7260-4124"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Abraham Chan","raw_affiliation_strings":["The University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077045048","display_name":"Arpan Gujarati","orcid":"https://orcid.org/0000-0002-2949-6826"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Arpan Gujarati","raw_affiliation_strings":["The University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073641368","display_name":"Karthik Pattabiraman","orcid":"https://orcid.org/0000-0003-2380-3415"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Karthik Pattabiraman","raw_affiliation_strings":["The University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103175261","display_name":"Sathish Gopalakrishnan","orcid":"https://orcid.org/0000-0003-2959-4802"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sathish Gopalakrishnan","raw_affiliation_strings":["The University of British Columbia, Vancouver, Canada"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia, Vancouver, Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091644091"],"corresponding_institution_ids":["https://openalex.org/I141945490"],"apc_list":null,"apc_paid":null,"fwci":1.5743,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.81687194,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1548","last_page":"1559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11309","display_name":"Music and Audio Processing","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9990000128746033,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9937000274658203,"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/diversity","display_name":"Diversity (politics)","score":0.704910933971405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5678954124450684},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.12554502487182617}],"concepts":[{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.704910933971405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5678954124450684},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.12554502487182617},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3672608.3707978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3672608.3707978","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3672608.3707978","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3672608.3707978","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2063387237","https://openalex.org/W2067713319","https://openalex.org/W2122892819","https://openalex.org/W2133824856","https://openalex.org/W2136189469","https://openalex.org/W2164655924","https://openalex.org/W2884928388","https://openalex.org/W2969560220","https://openalex.org/W2987861506","https://openalex.org/W3048817558","https://openalex.org/W3092703718","https://openalex.org/W3185323353","https://openalex.org/W4400089509"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Supervised":[0],"Machine":[1],"Learning":[2],"(ML)":[3],"is":[4],"used":[5],"in":[6],"many":[7,18,74],"safety-critical":[8],"applications,":[9],"such":[10],"as":[11],"self-driving":[12],"cars":[13],"and":[14,66,81,118,127,143,156],"medical":[15],"imaging.":[16],"Unfortunately,":[17],"training":[19,58,105],"datasets":[20,36],"have":[21],"been":[22],"discovered":[23],"to":[24,54,62,77,98,113,129],"contain":[25],"faults.":[26,107],"The":[27],"accuracy":[28,56,83,103],"of":[29,44,145],"individual":[30,159],"models":[31,46],"when":[32],"trained":[33],"with":[34,150],"faulty":[35],"can":[37,84],"significantly":[38,85],"degrade.":[39],"In":[40],"comparison,":[41],"ensembles,":[42,80,94],"consisting":[43],"multiple":[45],"combined":[47],"through":[48],"simple":[49],"majority":[50],"voting,":[51],"are":[52,67,73,165],"able":[53],"retain":[55],"despite":[57,104],"data":[59,106],"faults,":[60],"due":[61],"their":[63,82],"classification":[64],"diversity,":[65],"thus":[68],"more":[69,172],"resilient.":[70],"However,":[71],"there":[72],"different":[75,111],"ways":[76,112],"generate":[78,114],"ML":[79,116],"differ.":[86],"This":[87],"creates":[88],"a":[89,121],"large":[90],"search":[91,131],"space":[92],"for":[93,132],"making":[95],"it":[96,147],"challenging":[97],"find":[99],"ensembles":[100,146,161],"that":[101,123],"maximize":[102],"We":[108,135],"identify":[109],"three":[110],"diverse":[115],"models,":[117],"present":[119],"D-semble,":[120],"technique":[122],"uses":[124],"Genetic":[125],"Algorithms":[126],"diversity":[128],"efficiently":[130],"resilient":[133,173],"ensembles.":[134],"evaluate":[136],"D-semble":[137,164],"by":[138,163],"measuring":[139],"the":[140,157],"balanced":[141],"accuracies":[142],"F1-scores":[144],"finds.":[148],"Compared":[149],"bagging,":[151],"greedy":[152],"search,":[153],"random":[154],"selection,":[155],"best":[158],"model,":[160],"found":[162],"on":[166],"average":[167],"9%,":[168],"16%,":[169],"28%,":[170],"32%":[171],"respectively.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}