{"id":"https://openalex.org/W4293783406","doi":"https://doi.org/10.56553/popets-2022-0112","title":"Machine Learning with Differentially Private Labels: Mechanisms and Frameworks","display_name":"Machine Learning with Differentially Private Labels: Mechanisms and Frameworks","publication_year":2022,"publication_date":"2022-08-31","ids":{"openalex":"https://openalex.org/W4293783406","doi":"https://doi.org/10.56553/popets-2022-0112"},"language":"en","primary_location":{"id":"doi:10.56553/popets-2022-0112","is_oa":true,"landing_page_url":"https://doi.org/10.56553/popets-2022-0112","pdf_url":"https://petsymposium.org/popets/2022/popets-2022-0112.pdf","source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://petsymposium.org/popets/2022/popets-2022-0112.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101539896","display_name":"Xinyu Tang","orcid":"https://orcid.org/0000-0003-1761-6664"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Tang","raw_affiliation_strings":["Princeton University","Princeton Univer-sity,","Prince-ton University,","University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Princeton Univer-sity,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059480732","display_name":"Milad Nasr","orcid":"https://orcid.org/0000-0002-1913-6157"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Milad Nasr","raw_affiliation_strings":["University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","Prince-ton University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049153799","display_name":"Saeed Mahloujifar","orcid":"https://orcid.org/0000-0001-6586-8378"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Saeed Mahloujifar","raw_affiliation_strings":["Princeton University, E-mail: {sfar, liweis","Prince-ton University,","University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, E-mail: {sfar, liweis","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025710896","display_name":"Virat Shejwalkar","orcid":"https://orcid.org/0000-0003-4508-583X"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Virat Shejwalkar","raw_affiliation_strings":["University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","Prince-ton University,","Princeton Univer-sity,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Princeton Univer-sity,","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101908173","display_name":"Liwei Song","orcid":"https://orcid.org/0000-0003-4176-590X"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liwei Song","raw_affiliation_strings":["Princeton University, E-mail: {sfar, liweis","Prince-ton University,","University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, E-mail: {sfar, liweis","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018588864","display_name":"Amir Houmansadr","orcid":"https://orcid.org/0000-0002-7553-6657"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amir Houmansadr","raw_affiliation_strings":["University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","Princeton Univer-sity,","Prince-ton University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Massachusetts Amherst, E-mail: {milad, vshejwalkar","institution_ids":["https://openalex.org/I24603500"]},{"raw_affiliation_string":"Princeton Univer-sity,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103814915","display_name":"Prateek Mittal","orcid":null},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I24603500","display_name":"University of Massachusetts Amherst","ror":"https://ror.org/0072zz521","country_code":"US","type":"education","lineage":["https://openalex.org/I24603500"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prateek Mittal","raw_affiliation_strings":["Princeton University, E-mail: {sfar, liweis","Prince-ton University,","University of Massachusetts Amherst,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Princeton University, E-mail: {sfar, liweis","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"Prince-ton University,","institution_ids":["https://openalex.org/I20089843"]},{"raw_affiliation_string":"University of Massachusetts Amherst,","institution_ids":["https://openalex.org/I24603500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3121,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83368474,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2022","issue":"4","first_page":"332","last_page":"350"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9954000115394592,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9811000227928162,"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":0.7907067537307739},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6810447573661804},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6343663930892944},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6245988011360168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6191639304161072},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5296204686164856},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.45107027888298035},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.41240304708480835},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.41007620096206665},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32056725025177},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1331232786178589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7907067537307739},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6810447573661804},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6343663930892944},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6245988011360168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6191639304161072},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5296204686164856},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.45107027888298035},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41240304708480835},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.41007620096206665},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32056725025177},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1331232786178589},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.56553/popets-2022-0112","is_oa":true,"landing_page_url":"https://doi.org/10.56553/popets-2022-0112","pdf_url":"https://petsymposium.org/popets/2022/popets-2022-0112.pdf","source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.56553/popets-2022-0112","is_oa":true,"landing_page_url":"https://doi.org/10.56553/popets-2022-0112","pdf_url":"https://petsymposium.org/popets/2022/popets-2022-0112.pdf","source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1802365980","display_name":"Collaborative Research: SaTC: CORE: Medium: Towards Secure Federated Learning","funder_award_id":"2131910","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2800119129","display_name":null,"funder_award_id":"CNS-1553437","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2996961096","display_name":null,"funder_award_id":"CNS-1953786","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5165965387","display_name":"CAREER: Trustworthy Social Systems Using Network Science","funder_award_id":"1553437","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5334156545","display_name":"SaTC: CORE: Medium: Collaborative: A Linguistically-Informed Approach for Measuring and Circumventing Internet Censorship","funder_award_id":"1704105","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7034288922","display_name":"SaTC: CORE: Medium: Collaborative: Studying the Impact of IPv6 on Information Controls and Censorship Circumvention","funder_award_id":"1953786","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/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293783406.pdf","grobid_xml":"https://content.openalex.org/works/W4293783406.grobid-xml"},"referenced_works_count":87,"referenced_works":["https://openalex.org/W1534477342","https://openalex.org/W1658920975","https://openalex.org/W1686810756","https://openalex.org/W1992926795","https://openalex.org/W2013823004","https://openalex.org/W2019704260","https://openalex.org/W2027595342","https://openalex.org/W2030559796","https://openalex.org/W2051267297","https://openalex.org/W2052747341","https://openalex.org/W2054922243","https://openalex.org/W2070539708","https://openalex.org/W2095272373","https://openalex.org/W2099942492","https://openalex.org/W2101771965","https://openalex.org/W2108598243","https://openalex.org/W2109426455","https://openalex.org/W2119874464","https://openalex.org/W2129068307","https://openalex.org/W2167372639","https://openalex.org/W2194775991","https://openalex.org/W2294904676","https://openalex.org/W2378248953","https://openalex.org/W2461943168","https://openalex.org/W2473418344","https://openalex.org/W2532781556","https://openalex.org/W2535690855","https://openalex.org/W2765407302","https://openalex.org/W2777914285","https://openalex.org/W2784621220","https://openalex.org/W2785361959","https://openalex.org/W2788670714","https://openalex.org/W2803237185","https://openalex.org/W2804227495","https://openalex.org/W2898291644","https://openalex.org/W2898778923","https://openalex.org/W2905209730","https://openalex.org/W2947642149","https://openalex.org/W2950943617","https://openalex.org/W2951663308","https://openalex.org/W2962835266","https://openalex.org/W2963303354","https://openalex.org/W2963456518","https://openalex.org/W2963735582","https://openalex.org/W2963965291","https://openalex.org/W2964137095","https://openalex.org/W2964318098","https://openalex.org/W2987283559","https://openalex.org/W2996108195","https://openalex.org/W3001197829","https://openalex.org/W3005680577","https://openalex.org/W3030902227","https://openalex.org/W3035524453","https://openalex.org/W3036982689","https://openalex.org/W3039616371","https://openalex.org/W3045700442","https://openalex.org/W3100859887","https://openalex.org/W3102360395","https://openalex.org/W3110446398","https://openalex.org/W3118608800","https://openalex.org/W3134202462","https://openalex.org/W3169894107","https://openalex.org/W3185099774","https://openalex.org/W3212471751","https://openalex.org/W4205228770","https://openalex.org/W4249192582","https://openalex.org/W4287123801","https://openalex.org/W4287286018","https://openalex.org/W4288287974","https://openalex.org/W4297799122","https://openalex.org/W4298221930","https://openalex.org/W4394639701","https://openalex.org/W6632075054","https://openalex.org/W6640711881","https://openalex.org/W6676297131","https://openalex.org/W6676538461","https://openalex.org/W6678975374","https://openalex.org/W6684650931","https://openalex.org/W6687483927","https://openalex.org/W6720608135","https://openalex.org/W6745136726","https://openalex.org/W6747732332","https://openalex.org/W6755174528","https://openalex.org/W6764858589","https://openalex.org/W6764925846","https://openalex.org/W6790338629","https://openalex.org/W6792122116"],"related_works":["https://openalex.org/W2556319748","https://openalex.org/W3162567751","https://openalex.org/W4285260836","https://openalex.org/W4221088574","https://openalex.org/W2110287632","https://openalex.org/W3094076422","https://openalex.org/W3046775127","https://openalex.org/W4220686584","https://openalex.org/W4319309271","https://openalex.org/W2971361125"],"abstract_inverted_index":{"Label":[0],"differential":[1,7],"privacy":[2,8],"is":[3,58],"a":[4,33,36,39,71,76,142,149,178,213,257,267],"relaxation":[5],"of":[6,48,97,226,248],"for":[9,116,261],"machine":[10],"learning":[11,125,210],"scenarios":[12],"where":[13],"the":[14,17,27,49,101,137,168,183,192,197,216,228,233,242,246,263,278,296],"labels":[15,102,199,230],"are":[16,51,201],"only":[18,82,253],"sensitive":[19,59],"information":[20,60],"that":[21,73,151,200,290],"needs":[22],"to":[23,69,100,105,131,195,211,240,256,272,275,283],"be":[24],"protected":[25],"in":[26,38,103,170],"training":[28,117],"data.":[29],"For":[30],"example,":[31],"imagine":[32],"survey":[34],"from":[35],"participant":[37],"university":[40],"class":[41],"about":[42],"their":[43,55,83],"vaccination":[44,56,80],"status.":[45],"Some":[46],"attributes":[47],"students":[50],"publicly":[52],"available":[53],"but":[54],"status":[57],"and":[61,126,158,175,231],"must":[62],"remain":[63],"private.":[64],"Now":[65],"if":[66],"we":[67,86,112,207,244,252],"want":[68],"train":[70,212],"model":[72,180,193,214],"predicts":[74],"whether":[75],"student":[77],"has":[78],"received":[79],"using":[81,172,182,215,249],"public":[84],"information,":[85],"can":[87,293],"use":[88,94,208],"label-DP.":[89,300],"Recent":[90],"works":[91,298],"on":[92,299],"label-DP":[93,107,120],"different":[95],"ways":[96,225],"adding":[98,273],"noise":[99,134,169,188,255,274],"order":[104],"obtain":[106],"models.":[108],"In":[109],"this":[110,221],"work,":[111],"present":[113],"novel":[114],"techniques":[115,292],"models":[118],"with":[119,153,161,203,223,266],"guarantees":[121],"by":[122],"leveraging":[123],"unsupervised":[124,155,250],"semi-supervised":[127,209],"learning,":[128],"enabling":[129],"us":[130,282],"inject":[132],"less":[133,184,285],"while":[135],"obtaining":[136,227],"same":[138],"privacy,":[139],"therefore":[140],"achieving":[141],"better":[143],"utility-privacy":[144],"trade-off.":[145],"We":[146,219],"first":[147],"introduce":[148],"framework":[150,222],"starts":[152],"an":[154,237],"classifier":[156],"f0":[157,173,194],"dataset":[159],"D":[160],"noisy":[162,185,198,229],"label":[163,269],"set":[164],"Y":[165,171],",":[166,174],"reduces":[167],"then":[176],"trains":[177],"new":[179],"f":[181],"dataset.":[186],"Our":[187,287],"reduction":[189],"strategy":[190],"uses":[191],"remove":[196],"incorrect":[202],"high":[204],"probability.":[205],"Then":[206],"remaining":[217],"labels.":[218],"instantiate":[220],"multiple":[224],"also":[232],"base":[234],"classifier.":[235],"As":[236],"alternative":[238],"way":[239],"reduce":[241],"noise,":[243],"explore":[245],"effect":[247],"learning:":[251],"add":[254,284],"majority":[258],"voting":[259],"step":[260],"associating":[262],"learned":[264],"clusters":[265],"cluster":[268],"(as":[270],"opposed":[271],"individual":[276],"labels);":[277],"reduced":[279],"sensitivity":[280],"enables":[281],"noise.":[286],"experiments":[288],"show":[289],"these":[291],"significantly":[294],"outperform":[295],"prior":[297]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}