{"id":"https://openalex.org/W3044557501","doi":"https://doi.org/10.1145/3412815.3416881","title":"ADAGES","display_name":"ADAGES","publication_year":2020,"publication_date":"2020-10-15","ids":{"openalex":"https://openalex.org/W3044557501","doi":"https://doi.org/10.1145/3412815.3416881","mag":"3044557501"},"language":"en","primary_location":{"id":"doi:10.1145/3412815.3416881","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412815.3416881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.10776","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yu Gui","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Gui","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.2781,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65120266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.995199978351593,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6316999793052673},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5730000138282776},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5486000180244446},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.49320000410079956},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.4187999963760376},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.3889999985694885},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3605000078678131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678600013256073},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6316999793052673},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5730000138282776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5486000180244446},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.49320000410079956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43540000915527344},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.4187999963760376},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3889999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3626999855041504},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.33660000562667847},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C193244246","wikidata":"https://www.wikidata.org/wiki/Q5432696","display_name":"False discovery rate","level":3,"score":0.2777000069618225},{"id":"https://openalex.org/C2910001868","wikidata":"https://www.wikidata.org/wiki/Q458","display_name":"European union","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.26420000195503235}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3412815.3416881","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412815.3416881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.10776","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.10776","pdf_url":"https://arxiv.org/pdf/2007.10776","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:2007.10776","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.10776","pdf_url":"https://arxiv.org/pdf/2007.10776","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1596515083","https://openalex.org/W1933386641","https://openalex.org/W2074682976","https://openalex.org/W2109177042","https://openalex.org/W2110065044","https://openalex.org/W2135046866","https://openalex.org/W2805594262","https://openalex.org/W2896609429","https://openalex.org/W2964231067","https://openalex.org/W3000624331"],"related_works":[],"abstract_inverted_index":{"In":[0,55],"this":[1,56],"era":[2],"of":[3,11,85],"big":[4],"data,":[5],"not":[6],"only":[7],"the":[8,25,37,87,100],"large":[9],"amount":[10],"data":[12,20],"keeps":[13],"motivating":[14],"distributed":[15,28,43],"computing,":[16],"but":[17],"concerns":[18],"on":[19,27],"privacy":[21],"also":[22],"put":[23],"forward":[24],"emphasis":[26],"learning.":[29],"To":[30],"conduct":[31],"feature":[32,74],"selection":[33,75],"and":[34],"to":[35,71],"control":[36],"false":[38],"discovery":[39],"rate":[40],"in":[41,104],"a":[42,91],"pattern":[44],"with":[45,90],"multi-machines":[46],"or":[47],"multi-institutions,":[48],"an":[49,60],"efficient":[50],"aggregation":[51,62,102],"method":[52,63,82],"is":[53,83],"necessary.":[54],"paper,":[57],"we":[58],"propose":[59],"adaptive":[61],"called":[64],"ADAGES":[65],"which":[66],"can":[67],"be":[68],"flexibly":[69],"applied":[70],"any":[72],"machine-wise":[73],"method.":[76],"We":[77],"will":[78],"show":[79],"that":[80],"our":[81],"capable":[84],"controlling":[86],"overall":[88],"FDR":[89],"theoretical":[92],"foundation":[93],"while":[94],"maintaining":[95],"power":[96],"as":[97,99],"good":[98],"Union":[101],"rule":[103],"practice.":[105]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2020-07-29T00:00:00"}