{"id":"https://openalex.org/W4200394902","doi":"https://doi.org/10.1109/tnnls.2021.3129592","title":"Balancing Learning Model Privacy, Fairness, and Accuracy With Early Stopping Criteria","display_name":"Balancing Learning Model Privacy, Fairness, and Accuracy With Early Stopping Criteria","publication_year":2021,"publication_date":"2021-12-08","ids":{"openalex":"https://openalex.org/W4200394902","doi":"https://doi.org/10.1109/tnnls.2021.3129592","pmid":"https://pubmed.ncbi.nlm.nih.gov/34878980"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3129592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3129592","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101917791","display_name":"Tao Zhang","orcid":"https://orcid.org/0000-0003-4696-641X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tao Zhang","raw_affiliation_strings":["Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-4696-641X","affiliations":[{"raw_affiliation_string":"Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036801346","display_name":"Tianqing Zhu","orcid":"https://orcid.org/0000-0003-3411-7947"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tianqing Zhu","raw_affiliation_strings":["Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3411-7947","affiliations":[{"raw_affiliation_string":"Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709134","display_name":"Kun Gao","orcid":"https://orcid.org/0000-0001-8644-2157"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Kun Gao","raw_affiliation_strings":["Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Cyber Security and Privacy, School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051406984","display_name":"Wanlei Zhou","orcid":"https://orcid.org/0000-0002-1680-2521"},"institutions":[{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Wanlei Zhou","raw_affiliation_strings":["Institute of Data Science, City University of Macau, Macao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Data Science, City University of Macau, Macao, China","institution_ids":["https://openalex.org/I6469544"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"raw_orcid":"https://orcid.org/0000-0002-3491-5968","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":4.3437,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.94997829,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"34","issue":"9","first_page":"5557","last_page":"5569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9987999796867371,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9987999796867371,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9135000109672546,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.635793924331665},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.34823548793792725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33969026803970337}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.635793924331665},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.34823548793792725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33969026803970337}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3129592","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3129592","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:34878980","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34878980","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G2142201510","display_name":"III: Small: Exploiting the Massive User Generated Utterances for Intent Mining under Scarce Annotations","funder_award_id":"1909323","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3118254216","display_name":"III: Medium: Collaborative Research: An Extensible Heterogeneous Network Embedding Framework with Application Specific Adaptation","funder_award_id":"1763325","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4320322031","display_name":"III: Medium: Collaborative Research: Self-Supervised Recommender System Learning with Application Specific Adaption","funder_award_id":"2106758","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5189567976","display_name":"The right to be forgotten: GDPR modelling in cross-domain social networks ","funder_award_id":"DP200100946","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G6864170485","display_name":"Enhancing privacy preserving in dynamic cyberspace","funder_award_id":"DP190100981","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"},{"id":"https://openalex.org/G979281235","display_name":"SaTC: CORE: Small: Collaborative: Learning Dynamic and Robust Defenses Against Co-Adaptive Spammers","funder_award_id":"1930941","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1961345416","https://openalex.org/W2016043834","https://openalex.org/W2027595342","https://openalex.org/W2109426455","https://openalex.org/W2116666691","https://openalex.org/W2116984840","https://openalex.org/W2194775991","https://openalex.org/W2250539671","https://openalex.org/W2473418344","https://openalex.org/W2592232824","https://openalex.org/W2799159261","https://openalex.org/W2905029197","https://openalex.org/W2927692314","https://openalex.org/W2943618673","https://openalex.org/W2945302328","https://openalex.org/W2946346162","https://openalex.org/W2950943617","https://openalex.org/W2962790618","https://openalex.org/W2963367389","https://openalex.org/W2963626623","https://openalex.org/W2964235839","https://openalex.org/W2969261410","https://openalex.org/W2998690112","https://openalex.org/W3010220506","https://openalex.org/W3035616549","https://openalex.org/W3102360395","https://openalex.org/W3172100757","https://openalex.org/W3181858657","https://openalex.org/W3187057914","https://openalex.org/W3198112650","https://openalex.org/W3211490561","https://openalex.org/W4287329291","https://openalex.org/W4289129244","https://openalex.org/W4289258088","https://openalex.org/W4297795193","https://openalex.org/W4297799122","https://openalex.org/W4301904252","https://openalex.org/W6676639149","https://openalex.org/W6676984168","https://openalex.org/W6677855611","https://openalex.org/W6684072790","https://openalex.org/W6720710635","https://openalex.org/W6728551298","https://openalex.org/W6728897251","https://openalex.org/W6736002177","https://openalex.org/W6743595021","https://openalex.org/W6748256130","https://openalex.org/W6748377460","https://openalex.org/W6756847103","https://openalex.org/W6757410267","https://openalex.org/W6760993166","https://openalex.org/W6763088173","https://openalex.org/W6763192249","https://openalex.org/W6763290930","https://openalex.org/W6767236195","https://openalex.org/W6768690664","https://openalex.org/W6774427195","https://openalex.org/W6774668351","https://openalex.org/W6779537613","https://openalex.org/W6779949042","https://openalex.org/W6780805500","https://openalex.org/W6781511523","https://openalex.org/W6789778310","https://openalex.org/W6796914627","https://openalex.org/W7014198846"],"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":{"As":[0],"deep":[1,112,127],"learning":[2],"models":[3,76,115],"mature,":[4],"one":[5],"of":[6,32,39,48,55,91,99,108,131,152],"the":[7,16,27,30,37,50,106,129,145,150,180],"most":[8],"prescient":[9],"questions":[10],"we":[11,79,95,169],"face":[12],"is:":[13],"what":[14],"is":[15,57,134],"ideal":[17,195,206],"tradeoff":[18],"between":[19,52,140,208],"accuracy,":[20],"fairness,":[21],"and":[22,29,45,103,119],"privacy":[23,28],"(AFP)?":[24],"Unfortunately,":[25],"both":[26,101],"fairness":[31,82],"a":[33,97,138,156,188],"model":[34,153,189],"come":[35],"at":[36,155,183],"cost":[38],"its":[40],"accuracy.":[41,164],"Hence,":[42,94],"an":[43,88,205],"efficient":[44],"effective":[46],"means":[47],"fine-tuning":[49],"balance":[51,139,207],"this":[53,92,167],"trinity":[54],"needs":[56],"critical.":[58],"Motivated":[59],"by":[60],"some":[61],"curious":[62],"observations":[63],"in":[64,111,126,163],"privacy-accuracy":[65],"tradeoffs":[66],"with":[67],"differentially":[68],"private":[69],"stochastic":[70],"gradient":[71,117],"descent":[72],"(DP-SGD),":[73],"where":[74],"fair":[75],"sometimes":[77],"result,":[78],"conjecture":[80],"that":[81,200],"might":[83],"be":[84],"better":[85],"managed":[86],"as":[87,191],"indirect":[89],"byproduct":[90],"process.":[93],"conduct":[96],"series":[98],"analyses,":[100],"theoretical":[102],"empirical,":[104],"on":[105,166],"impacts":[107],"implementing":[109],"DP-SGD":[110,143],"neural":[113],"network":[114],"through":[116],"clipping":[118],"noise":[120],"addition.":[121],"The":[122],"results":[123],"show":[124,199],"that,":[125],"learning,":[128],"number":[130],"training":[132,146,187],"epochs":[133],"central":[135],"to":[136,176,185,192],"striking":[137],"AFP":[141],"because":[142],"makes":[144],"less":[147],"stable,":[148],"providing":[149],"possibility":[151],"updates":[154],"low":[157],"discrimination":[158],"level":[159],"without":[160],"much":[161],"loss":[162],"Based":[165],"observation,":[168],"designed":[170],"two":[171],"different":[172],"early":[173],"stopping":[174],"criteria":[175],"help":[177],"analysts":[178],"choose":[179],"optimal":[181],"epoch":[182],"which":[184],"stop":[186],"so":[190],"achieve":[193,204],"their":[194],"tradeoff.":[196],"Extensive":[197],"experiments":[198],"our":[201],"methods":[202],"can":[203],"AFP.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}