{"id":"https://openalex.org/W2979501239","doi":null,"title":"Privacy-Preserving Contextual Bandits.","display_name":"Privacy-Preserving Contextual Bandits.","publication_year":2019,"publication_date":"2019-10-11","ids":{"openalex":"https://openalex.org/W2979501239","mag":"2979501239"},"language":"en","primary_location":{"id":"mag:2979501239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.05299","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.05299","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087325198","display_name":"Awni Hannun","orcid":"https://orcid.org/0000-0003-3080-4002","observed_orcids":["https://orcid.org/0000-0003-3080-4002"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Awni Hannun","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3080-4002","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000913628","display_name":"Brian Knott","orcid":"https://orcid.org/0009-0005-9196-4300","observed_orcids":["https://orcid.org/0009-0005-9196-4300"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brian Knott","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003509810","display_name":"Shubho Sengupta","orcid":"https://orcid.org/0009-0007-4204-5185","observed_orcids":["https://orcid.org/0009-0007-4204-5185"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shubho Sengupta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5109065097","display_name":"Laurens J. P. van der Maaten","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laurens van der Maaten","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.7240999937057495,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.7240999937057495,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.27390000224113464,"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/T10237","display_name":"Cryptography and Data Security","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/contextual-bandits","display_name":"contextual bandits","score":0.9359999895095825},{"id":"https://openalex.org/keywords/privacy-preserving-machine-learning","display_name":"privacy-preserving machine learning","score":0.7730000019073486},{"id":"https://openalex.org/keywords/secure-multi-party-computation","display_name":"secure multi-party computation","score":0.9070000052452087},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"differential privacy","score":0.9950000047683716},{"id":"https://openalex.org/keywords/epsilon-greedy-exploration","display_name":"epsilon-greedy exploration","score":0.9810000061988831},{"id":"https://openalex.org/keywords/arm-selection","display_name":"arm selection","score":0.4959999918937683},{"id":"https://openalex.org/keywords/recommender-systems","display_name":"recommender systems","score":0.4339999854564667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.720496416091919},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6715454459190369},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.5876225829124451},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.48062819242477417},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.46156495809555054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36144182085990906},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.33638641238212585},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2857072055339813},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2591094970703125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.11319416761398315}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2979501239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.05299","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2979501239","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1910.05299","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3005996602","https://openalex.org/W2890884856","https://openalex.org/W3088648627","https://openalex.org/W3093548068","https://openalex.org/W4226096719","https://openalex.org/W6948042188","https://openalex.org/W7124314137","https://openalex.org/W4408354925","https://openalex.org/W4296591815","https://openalex.org/W7203889945"],"abstract_inverted_index":{"Contextual":[0,37],"bandits":[1,38],"are":[2,39],"online":[3],"learners":[4],"that,":[5],"given":[6],"an":[7,10],"input,":[8],"select":[9],"arm":[11,121,129],"and":[12,27],"receive":[13],"a":[14,24,51,61,66,150,161],"reward":[15,22,33,76,136,145],"for":[16],"that":[17,102,108,155],"arm.":[18],"They":[19],"use":[20],"the":[21,31,35,69,74,85,91,105,117,120,135,138,144],"as":[23],"learning":[25,52],"signal":[26],"aim":[28,58,71],"to":[29,42,59,72,81,99],"maximize":[30,73],"total":[32,75],"over":[34],"inputs.":[36],"commonly":[40],"used":[41],"solve":[43],"recommendation":[44],"or":[45],"ranking":[46],"problems.":[47],"This":[48,147],"paper":[49,148],"considers":[50],"setting":[53],"in":[54,65,169],"which":[55,128],"multiple":[56,95],"parties":[57,70,96,118,124,140],"train":[60],"contextual":[62,152,170],"bandit":[63,153],"together":[64],"private":[67,163],"way:":[68],"but":[77,107,122,137],"do":[78],"not":[79,126,142],"want":[80],"share":[82],"any":[83],"of":[84,116],"relevant":[86],"information":[87],"they":[88],"possess":[89],"with":[90,112,160],"other":[92,113,123,139],"parties.":[93,114],"Specifically,":[94],"have":[97],"access":[98],"(different)":[100],"features":[101],"may":[103,125,141],"benefit":[104],"learner":[106],"cannot":[109],"be":[110],"shared":[111],"One":[115,132],"pulls":[119],"learn":[127,143],"was":[130],"pulled.":[131],"party":[133],"receives":[134],"value.":[146],"develops":[149],"privacy-preserving":[151],"algorithm":[154],"combines":[156],"secure":[157],"multi-party":[158],"computation":[159],"differential":[162],"mechanism":[164],"based":[165],"on":[166],"epsilon-greedy":[167],"exploration":[168],"bandits.":[171]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2019-10-18T00:00:00"}
