{"id":"https://openalex.org/W2889434690","doi":"https://doi.org/10.1109/ssp.2018.8450839","title":"Differential Privacy for Positive and Unlabeled Learning With Known Class Priors","display_name":"Differential Privacy for Positive and Unlabeled Learning With Known Class Priors","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2889434690","doi":"https://doi.org/10.1109/ssp.2018.8450839","mag":"2889434690"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2018.8450839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","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/A5101588169","display_name":"Anh T. Pham","orcid":"https://orcid.org/0000-0003-3898-2727"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Anh T. Pham","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008398853","display_name":"Raviv Raich","orcid":"https://orcid.org/0000-0001-9711-5709"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raviv Raich","raw_affiliation_strings":["School of EECS, Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"School of EECS, Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101588169"],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":0.3257,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67424708,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"83","issue":null,"first_page":"85","last_page":"89"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9993000030517578,"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":0.9993000030517578,"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":0.9991000294685364,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9944999814033508,"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/differential-privacy","display_name":"Differential privacy","score":0.9228238463401794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7099011540412903},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6509571075439453},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6382783651351929},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5679901838302612},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5674851536750793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5364713072776794},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5255191326141357},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.4956923723220825},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.45211634039878845},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4425089955329895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4406859874725342},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3320017457008362},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.0862981379032135}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.9228238463401794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7099011540412903},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6509571075439453},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6382783651351929},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5679901838302612},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5674851536750793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5364713072776794},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5255191326141357},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.4956923723220825},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.45211634039878845},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4425089955329895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4406859874725342},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3320017457008362},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0862981379032135},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp.2018.8450839","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450839","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","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":27,"referenced_works":["https://openalex.org/W303151045","https://openalex.org/W1703735685","https://openalex.org/W1825821140","https://openalex.org/W1969623397","https://openalex.org/W1978033244","https://openalex.org/W1982032418","https://openalex.org/W2027595342","https://openalex.org/W2060036647","https://openalex.org/W2095345875","https://openalex.org/W2112380340","https://openalex.org/W2113290770","https://openalex.org/W2127883478","https://openalex.org/W2132442585","https://openalex.org/W2466501638","https://openalex.org/W2537231727","https://openalex.org/W2765409832","https://openalex.org/W2962745351","https://openalex.org/W2963404486","https://openalex.org/W3120740533","https://openalex.org/W6637474009","https://openalex.org/W6657138077","https://openalex.org/W6676639149","https://openalex.org/W6677082149","https://openalex.org/W6679102953","https://openalex.org/W6717319918","https://openalex.org/W6720067423","https://openalex.org/W6729244039"],"related_works":["https://openalex.org/W2133556223","https://openalex.org/W121244246","https://openalex.org/W2378187833","https://openalex.org/W2504719182","https://openalex.org/W4309984931","https://openalex.org/W4282977123","https://openalex.org/W192740413","https://openalex.org/W1473009882","https://openalex.org/W2364325338","https://openalex.org/W4294974824"],"abstract_inverted_index":{"Despite":[0],"the":[1,38,44,101,125,129,142,152,156],"increasing":[2],"attention":[3],"to":[4,19,71,141],"big":[5],"data,":[6],"there":[7],"are":[8,41,160],"several":[9],"domains":[10,67,86],"where":[11,155],"labeled":[12,79],"data":[13,24,64,83],"is":[14,87,96,133],"scarce":[15],"or":[16],"too":[17],"costly":[18],"obtain.":[20],"For":[21],"example,":[22],"for":[23,113,124,151],"from":[25,37,65,76,84],"information":[26],"retrieval,":[27],"gene":[28],"analysis,":[29,33],"and":[30,54,61,90,115,158,163],"social":[31],"network":[32],"only":[34,77],"training":[35,47,93],"samples":[36,48,94],"positive":[39,53,60,114],"class":[40,130],"annotated":[42],"while":[43],"remaining":[45],"unlabeled":[46,52,55,62,116],"consist":[49],"of":[50,103,139],"both":[51,161],"negative":[56],"samples.":[57],"The":[58],"specific":[59],"(PU)":[63],"those":[66,85],"necessitates":[68],"a":[69,73,109,121,136,148],"mechanism":[70,150],"learn":[72],"two-class":[74],"classifier":[75],"one-class":[78],"data.":[80,117],"Moreover,":[81],"because":[82],"highly":[88],"sensitive":[89],"private,":[91],"preserving":[92],"privacy":[95,157],"essential.":[97],"This":[98],"paper":[99],"addresses":[100],"challenge":[102],"private":[104,111],"PU":[105,126],"learning":[106,122],"by":[107],"designing":[108],"differentially":[110],"algorithm":[112],"We":[118,145],"first":[119],"propose":[120,147],"framework":[123,154],"setting":[127],"when":[128],"prior":[131],"probability":[132],"known,":[134],"with":[135],"theoretical":[137],"guarantee":[138],"convergence":[140],"optimal":[143],"classifier.":[144],"then":[146],"privacy-preserving":[149],"designed":[153],"utility":[159],"theoretically":[162],"empirically":[164],"proved.":[165]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
