{"id":"https://openalex.org/W4307823742","doi":"https://doi.org/10.1145/3560827.3563375","title":"Efficient and Accurate Homomorphic Comparisons","display_name":"Efficient and Accurate Homomorphic Comparisons","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4307823742","doi":"https://doi.org/10.1145/3560827.3563375"},"language":"en","primary_location":{"id":"doi:10.1145/3560827.3563375","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3560827.3563375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Workshop on Encrypted Computing &amp; Applied Homomorphic Cryptography","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://cea.hal.science/cea-03983178","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026677802","display_name":"Olive Chakraborty","orcid":"https://orcid.org/0000-0003-0396-908X"},"institutions":[{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Olive Chakraborty","raw_affiliation_strings":["CEA, Paris, France"],"affiliations":[{"raw_affiliation_string":"CEA, Paris, France","institution_ids":["https://openalex.org/I2738703131"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059453440","display_name":"Martin Zuber","orcid":"https://orcid.org/0000-0003-0669-6486"},"institutions":[{"id":"https://openalex.org/I2738703131","display_name":"Commissariat \u00e0 l'\u00c9nergie Atomique et aux \u00c9nergies Alternatives","ror":"https://ror.org/00jjx8s55","country_code":"FR","type":"funder","lineage":["https://openalex.org/I2738703131"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Martin Zuber","raw_affiliation_strings":["CEA, Paris, France"],"affiliations":[{"raw_affiliation_string":"CEA, Paris, France","institution_ids":["https://openalex.org/I2738703131"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026677802"],"corresponding_institution_ids":["https://openalex.org/I2738703131"],"apc_list":null,"apc_paid":null,"fwci":1.388,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84469247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"46"},"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/T10237","display_name":"Cryptography and Data Security","score":0.9983999729156494,"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":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.8865759372711182},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.812075138092041},{"id":"https://openalex.org/keywords/homomorphic-encryption","display_name":"Homomorphic encryption","score":0.7704411745071411},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.7042515277862549},{"id":"https://openalex.org/keywords/logarithm","display_name":"Logarithm","score":0.6051080822944641},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.45079994201660156},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.44046926498413086},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4224895238876343},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41395020484924316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3542833924293518},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34040898084640503},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1772398054599762},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09985598921775818}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8865759372711182},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.812075138092041},{"id":"https://openalex.org/C158338273","wikidata":"https://www.wikidata.org/wiki/Q2154943","display_name":"Homomorphic encryption","level":3,"score":0.7704411745071411},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.7042515277862549},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.6051080822944641},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45079994201660156},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.44046926498413086},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4224895238876343},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41395020484924316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3542833924293518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34040898084640503},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1772398054599762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09985598921775818},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3560827.3563375","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3560827.3563375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th Workshop on Encrypted Computing &amp; Applied Homomorphic Cryptography","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:cea-03983178v1","is_oa":true,"landing_page_url":"https://cea.hal.science/cea-03983178","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WAHC'22: Proceedings of the 10th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, 2022, ACM, pp.35-46, 2022, WAHC'22 - Proceedings of the 10th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, 978-1-4503-9877-0. &#x27E8;10.1145/3560827.3563375&#x27E9;","raw_type":"Proceedings"}],"best_oa_location":{"id":"pmh:oai:HAL:cea-03983178v1","is_oa":true,"landing_page_url":"https://cea.hal.science/cea-03983178","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WAHC'22: Proceedings of the 10th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, 2022, ACM, pp.35-46, 2022, WAHC'22 - Proceedings of the 10th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, 978-1-4503-9877-0. &#x27E8;10.1145/3560827.3563375&#x27E9;","raw_type":"Proceedings"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1718986858","display_name":null,"funder_award_id":"ANR-22-PECY-000","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G8231686437","display_name":null,"funder_award_id":"ANR-22-PECY-0003","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2031533839","https://openalex.org/W2132172731","https://openalex.org/W2400700555","https://openalex.org/W2554750353","https://openalex.org/W2747329762","https://openalex.org/W2768505000","https://openalex.org/W2942255051","https://openalex.org/W3036496141","https://openalex.org/W3134663857","https://openalex.org/W3151268345","https://openalex.org/W3157813311"],"related_works":["https://openalex.org/W4386603768","https://openalex.org/W2950475743","https://openalex.org/W2886711096","https://openalex.org/W2152926062","https://openalex.org/W2949607150","https://openalex.org/W2950312267","https://openalex.org/W3123945077","https://openalex.org/W2398715209","https://openalex.org/W3203896436","https://openalex.org/W913176383"],"abstract_inverted_index":{"We":[0],"design":[1],"and":[2,7,59,79,83],"implement":[3],"a":[4,26,74],"new":[5],"efficient":[6],"accurate":[8],"fully":[9],"homomorphic":[10],"argmin/min":[11],"or":[12],"argmax/max":[13],"comparison":[14],"operator,":[15],"which":[16,86],"finds":[17],"its":[18],"application":[19],"in":[20],"numerous":[21],"real-world":[22],"use":[23],"cases":[24],"as":[25],"classifier.":[27],"In":[28],"particular":[29],"we":[30,95],"propose":[31],"two":[32],"versions":[33],"of":[34,51,77,99],"our":[35,93],"algorithms":[36],"using":[37,92],"different":[38],"tools":[39],"from":[40],"TFHE's":[41],"functional":[42],"bootstrapping":[43],"toolkit.":[44],"Our":[45,62],"algorithm":[46,63],"scales":[47],"to":[48],"any":[49],"number":[50],"input":[52],"data":[53],"points":[54],"with":[55,73],"linear":[56],"time":[57],"complexity":[58],"logarithmic":[60],"noise-propagation.":[61],"is":[64],"the":[65,68,89],"fastest":[66],"on":[67],"market":[69],"for":[70,102],"non-parallel":[71],"comparisons":[72],"high":[75],"degree":[76],"accuracy":[78,98],"precision.":[80],"For":[81],"MNIST":[82],"SVHN":[84],"datasets,":[85],"work":[87],"under":[88],"PATE":[90],"framework,":[91],"algorithm,":[94],"achieve":[96],"an":[97],"around":[100],"99.95%":[101],"both.":[103]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
