{"id":"https://openalex.org/W4415367078","doi":"https://doi.org/10.1109/isit63088.2025.11195531","title":"Federated One-Shot Learning with Data Privacy and Objective-Hiding","display_name":"Federated One-Shot Learning with Data Privacy and Objective-Hiding","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4415367078","doi":"https://doi.org/10.1109/isit63088.2025.11195531"},"language":null,"primary_location":{"id":"doi:10.1109/isit63088.2025.11195531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","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/A5019059202","display_name":"Maximilian Egger","orcid":"https://orcid.org/0000-0003-2677-4074"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Maximilian Egger","raw_affiliation_strings":["Technical University of Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058759310","display_name":"R\u00fcdiger Urbanke","orcid":"https://orcid.org/0000-0002-4839-821X"},"institutions":[{"id":"https://openalex.org/I142476485","display_name":"\u00c9cole Polytechnique","ror":"https://ror.org/05hy3tk52","country_code":"FR","type":"education","lineage":["https://openalex.org/I142476485","https://openalex.org/I4210145102"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"R\u00fcdiger Urbanke","raw_affiliation_strings":["&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de,Lausanne,Switzerland"],"affiliations":[{"raw_affiliation_string":"&#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de,Lausanne,Switzerland","institution_ids":["https://openalex.org/I142476485"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024768934","display_name":"Rawad Bitar","orcid":"https://orcid.org/0000-0002-4421-1024"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rawad Bitar","raw_affiliation_strings":["Technical University of Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019059202"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15411696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9890000224113464,"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":0.9890000224113464,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9653000235557556,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9545000195503235,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/protocol","display_name":"Protocol (science)","score":0.6496000289916992},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5935999751091003},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.5824999809265137},{"id":"https://openalex.org/keywords/safeguarding","display_name":"Safeguarding","score":0.5698999762535095},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.546500027179718},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5163000226020813},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4999000132083893},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.45419999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8356000185012817},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.6496000289916992},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5935999751091003},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.5824999809265137},{"id":"https://openalex.org/C2776743756","wikidata":"https://www.wikidata.org/wiki/Q5097921","display_name":"Safeguarding","level":2,"score":0.5698999762535095},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.546500027179718},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5163000226020813},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3564000129699707},{"id":"https://openalex.org/C18396474","wikidata":"https://www.wikidata.org/wiki/Q2465888","display_name":"Secure multi-party computation","level":3,"score":0.335999995470047},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C509729295","wikidata":"https://www.wikidata.org/wiki/Q7246032","display_name":"Privacy software","level":3,"score":0.3314000070095062},{"id":"https://openalex.org/C102938260","wikidata":"https://www.wikidata.org/wiki/Q1999831","display_name":"Privacy policy","level":3,"score":0.3287999927997589},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.3278999924659729},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C3017597292","wikidata":"https://www.wikidata.org/wiki/Q25052250","display_name":"Privacy protection","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.29420000314712524},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2818000018596649},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.28130000829696655}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit63088.2025.11195531","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3962700909","display_name":null,"funder_award_id":"BI 2492/1-1,WA 3907/7-1","funder_id":"https://openalex.org/F4320308022","funder_display_name":"California Department of Fish and Game"}],"funders":[{"id":"https://openalex.org/F4320308022","display_name":"California Department of Fish and Game","ror":"https://ror.org/02v6w2r95"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W2073346043","https://openalex.org/W2158275940","https://openalex.org/W2767079719","https://openalex.org/W2789160219","https://openalex.org/W2886411684","https://openalex.org/W2888732914","https://openalex.org/W2906543194","https://openalex.org/W2911978475","https://openalex.org/W2940288022","https://openalex.org/W2963032222","https://openalex.org/W2963413537","https://openalex.org/W2964081636","https://openalex.org/W2964177287","https://openalex.org/W2976078580","https://openalex.org/W2976277185","https://openalex.org/W2976399918","https://openalex.org/W2990789045","https://openalex.org/W2995022099","https://openalex.org/W3010436063","https://openalex.org/W3013310637","https://openalex.org/W3044113996","https://openalex.org/W3045672834","https://openalex.org/W3049183470","https://openalex.org/W3080316257","https://openalex.org/W3096328345","https://openalex.org/W3102031770","https://openalex.org/W3167681863","https://openalex.org/W3191104470","https://openalex.org/W3198593204","https://openalex.org/W3209696639","https://openalex.org/W3214428243","https://openalex.org/W4210725882","https://openalex.org/W4226549547","https://openalex.org/W4289655453","https://openalex.org/W4309080560","https://openalex.org/W4321020874","https://openalex.org/W4323065158","https://openalex.org/W4383112472","https://openalex.org/W4386066579","https://openalex.org/W4386075204","https://openalex.org/W4387105517","https://openalex.org/W4387337829","https://openalex.org/W4392086562","https://openalex.org/W4410358889","https://openalex.org/W4414158983"],"related_works":[],"abstract_inverted_index":{"Privacy":[0],"in":[1,56,95,118],"federated":[2],"learning":[3],"is":[4,140],"crucial,":[5],"encompassing":[6],"two":[7],"key":[8],"aspects:":[9],"safeguarding":[10],"the":[11,18,21,25,28,35,103,115,121,129,132,138,164,170],"privacy":[12,19,67,130],"of":[13,20,131,137,166],"clients'":[14,133],"data":[15],"and":[16,59,117,150],"maintaining":[17],"federator's":[22],"objective":[23,126],"from":[24,54,169],"clients.":[26],"While":[27],"first":[29],"aspect":[30],"has":[31,37],"been":[32],"extensively":[33],"studied,":[34],"second":[36],"received":[38],"much":[39],"less":[40],"attention.":[41],"We":[42,158],"present":[43],"a":[44,141,151],"novel":[45,152],"approach":[46,93],"that":[47,145,160],"addresses":[48],"both":[49],"concerns":[50],"simultaneously,":[51],"drawing":[52],"inspiration":[53],"techniques":[55],"knowledge":[57],"distillation":[58],"private":[60,70,154],"information":[61,155],"retrieval":[62,156],"to":[63,83],"provide":[64],"strong":[65],"information-theoretic":[66],"guarantees.":[68],"Traditional":[69],"function":[71],"computation":[72,149],"methods":[73],"could":[74],"be":[75],"used":[76],"here;":[77],"however,":[78],"they":[79],"are":[80,112],"typically":[81],"limited":[82],"linear":[84],"or":[85],"polynomial":[86],"functions.":[87],"To":[88],"overcome":[89],"these":[90,110],"constraints,":[91],"our":[92,161],"unfolds":[94],"three":[96],"stages.":[97],"In":[98,107],"Stage":[99,108,119],"0,":[100],"clients":[101],"perform":[102],"necessary":[104],"computations":[105],"locally.":[106],"1,":[109],"results":[111],"shared":[113],"among":[114],"clients,":[116],"2,":[120],"federator":[122],"retrieves":[123],"its":[124],"desired":[125],"without":[127],"compromising":[128],"data.":[134],"The":[135],"crux":[136],"method":[139,162],"carefully":[142],"designed":[143],"protocol":[144],"combines":[146],"secret-sharing-based":[147],"multi-party":[148],"graph-based":[153],"scheme.":[157],"show":[159],"outperforms":[163],"use":[165],"existing":[167],"tools":[168],"literature.":[171]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-21T00:00:00"}
