{"id":"https://openalex.org/W4404644653","doi":"https://doi.org/10.1145/3689932.3694760","title":"Feature Selection from Differentially Private Correlations","display_name":"Feature Selection from Differentially Private Correlations","publication_year":2024,"publication_date":"2024-11-06","ids":{"openalex":"https://openalex.org/W4404644653","doi":"https://doi.org/10.1145/3689932.3694760"},"language":"en","primary_location":{"id":"doi:10.1145/3689932.3694760","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3689932.3694760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"},"type":"article","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/A5091019606","display_name":"Ryan Swope","orcid":null},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ryan Swope","raw_affiliation_strings":["Booz Allen Hamilton, Philadelphia, PA, USA"],"raw_orcid":"https://orcid.org/0009-0007-7103-3132","affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086021685","display_name":"Amol Khanna","orcid":"https://orcid.org/0000-0002-5566-095X"},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amol Khanna","raw_affiliation_strings":["Booz Allen Hamilton, Boston, MA, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-5566-095X","affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton, Boston, MA, United States of America","institution_ids":["https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058512869","display_name":"Philip Doldo","orcid":"https://orcid.org/0000-0002-9039-7966"},"institutions":[{"id":"https://openalex.org/I1322124587","display_name":"Booz Allen Hamilton (United States)","ror":"https://ror.org/051rcp357","country_code":"US","type":"company","lineage":["https://openalex.org/I1322124587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Doldo","raw_affiliation_strings":["Booz Allen Hamilton, Annapolis Junction, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-9039-7966","affiliations":[{"raw_affiliation_string":"Booz Allen Hamilton, Annapolis Junction, MD, USA","institution_ids":["https://openalex.org/I1322124587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113293391","display_name":"Saptarshi Roy","orcid":"https://orcid.org/0000-0003-4183-205X"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saptarshi Roy","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0003-4183-205X","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068036546","display_name":"Edward Raff","orcid":"https://orcid.org/0000-0002-9900-1972"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edward Raff","raw_affiliation_strings":["Booz Allen Hamiltion &amp; University of Maryland, Baltimore County, Syracuse, NY, United States of America"],"raw_orcid":"https://orcid.org/0000-0002-9900-1972","affiliations":[{"raw_affiliation_string":"Booz Allen Hamiltion &amp; University of Maryland, Baltimore County, Syracuse, NY, United States of America","institution_ids":["https://openalex.org/I79272384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4082,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64114257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.998199999332428,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9948999881744385,"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/feature-selection","display_name":"Feature selection","score":0.7217044830322266},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5836917161941528},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5539667010307312},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5513797998428345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41627562046051025},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3991742432117462}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7217044830322266},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5836917161941528},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5539667010307312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5513797998428345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41627562046051025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3991742432117462},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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":1,"locations":[{"id":"doi:10.1145/3689932.3694760","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3689932.3694760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Workshop on Artificial Intelligence and Security","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1498372169","https://openalex.org/W1596936080","https://openalex.org/W1727290854","https://openalex.org/W1979377971","https://openalex.org/W2004915807","https://openalex.org/W2035820295","https://openalex.org/W2051434435","https://openalex.org/W2053992818","https://openalex.org/W2064208261","https://openalex.org/W2068517117","https://openalex.org/W2076356585","https://openalex.org/W2077359776","https://openalex.org/W2082290707","https://openalex.org/W2087684630","https://openalex.org/W2099641086","https://openalex.org/W2101386839","https://openalex.org/W2108943779","https://openalex.org/W2114515438","https://openalex.org/W2130410032","https://openalex.org/W2135046866","https://openalex.org/W2138218344","https://openalex.org/W2154332973","https://openalex.org/W2154560360","https://openalex.org/W2156809732","https://openalex.org/W2159400887","https://openalex.org/W2167689714","https://openalex.org/W2168561598","https://openalex.org/W2549852765","https://openalex.org/W2604272474","https://openalex.org/W2619567144","https://openalex.org/W2912099989","https://openalex.org/W2949078246","https://openalex.org/W2965870078","https://openalex.org/W2997591727","https://openalex.org/W4210643453","https://openalex.org/W4212774754","https://openalex.org/W4293581666","https://openalex.org/W4294541781","https://openalex.org/W4295946216","https://openalex.org/W4388886454"],"related_works":["https://openalex.org/W4205762803","https://openalex.org/W2535856026","https://openalex.org/W2265065644","https://openalex.org/W3147584709","https://openalex.org/W2134699697","https://openalex.org/W3017188156","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Data":[0],"scientists":[1],"often":[2],"seek":[3],"to":[4,85,95,105],"identify":[5],"the":[6,48,58,108,124],"most":[7],"important":[8,97],"features":[9,98],"in":[10,39],"high-dimensional":[11,28,31],"datasets.":[12,29,133],"This":[13,71],"can":[14,23,33],"be":[15],"done":[16],"through":[17],"L":[18],"1-regularized":[19],"regression,":[20],"but":[21],"this":[22,43],"become":[24],"inefficient":[25],"for":[26,52,127],"very":[27],"Additionally,":[30],"regression":[32],"leak":[34,112],"information":[35,113],"about":[36,114],"individual":[37,115],"datapoints":[38],"a":[40,82,91,100],"dataset.":[41],"In":[42],"paper,":[44],"we":[45,80],"empirically":[46],"evaluate":[47],"established":[49,125],"baseline":[50,126],"method":[51,121],"feature":[53,87,129],"selection":[54,60,130],"with":[55],"differential":[56],"privacy,":[57],"two-stage":[59],"technique,":[61],"and":[62,102],"show":[63],"that":[64,107,119],"it":[65,73],"is":[66],"not":[67,111],"stable":[68],"under":[69],"sparsity.":[70],"makes":[72],"perform":[74],"poorly":[75],"on":[76,131],"real-world":[77],"datasets,":[78],"so":[79],"consider":[81],"different":[83],"approach":[84],"private":[86,128],"selection.":[88],"We":[89,117],"employ":[90],"correlations-based":[92],"order":[93],"statistic":[94],"choose":[96],"from":[99],"dataset":[101],"privatize":[103],"them":[104],"ensure":[106],"results":[109],"do":[110],"datapoints.":[116],"find":[118],"our":[120],"significantly":[122],"outperforms":[123],"many":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
