{"id":"https://openalex.org/W6894094718","doi":"https://doi.org/10.5281/zenodo.7897618","title":"Certified Private Inference on Neural Networks via Lipschitz-Guided Abstraction Refinement","display_name":"Certified Private Inference on Neural Networks via Lipschitz-Guided Abstraction Refinement","publication_year":2023,"publication_date":"2023-05-04","ids":{"openalex":"https://openalex.org/W6894094718","doi":"https://doi.org/10.5281/zenodo.7897618"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.7897618","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.7897618","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.7897618","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Manino, Edoardo","orcid":"https://orcid.org/0000-0003-0028-5440"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Manino, Edoardo","raw_affiliation_strings":["The University of Manchester"],"raw_orcid":"https://orcid.org/0000-0003-0028-5440","affiliations":[{"raw_affiliation_string":"The University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Magri, Bernardo","orcid":"https://orcid.org/0000-0003-4537-7023"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Magri, Bernardo","raw_affiliation_strings":["The University of Manchester"],"raw_orcid":"https://orcid.org/0000-0003-4537-7023","affiliations":[{"raw_affiliation_string":"The University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mustafa, Mustafa A.","orcid":"https://orcid.org/0000-0002-8772-8023"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mustafa, Mustafa A.","raw_affiliation_strings":["The University of Manchester"],"raw_orcid":"https://orcid.org/0000-0002-8772-8023","affiliations":[{"raw_affiliation_string":"The University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":null,"display_name":"Cordeiro, Lucas","orcid":"https://orcid.org/0000-0002-6235-4272"},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Cordeiro, Lucas","raw_affiliation_strings":["The University of Manchester"],"raw_orcid":"https://orcid.org/0000-0002-6235-4272","affiliations":[{"raw_affiliation_string":"The University of Manchester","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.685699999332428},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5898000001907349},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.5584999918937683},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.531499981880188},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5055000185966492},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4828000068664551},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47760000824928284},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.36079999804496765}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.685699999332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6517999768257141},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5898000001907349},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5055000185966492},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4828000068664551},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4041000008583069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3691999912261963},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3481999933719635},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2842999994754791},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.2782000005245209},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.2773999869823456},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.25859999656677246}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5281/zenodo.7897618","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.7897618","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.5281/zenodo.7897618","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.7897618","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.5227783918380737}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Private":[0],"inference":[1,50],"on":[2,10,99,120,155],"neural":[3,14,77,157],"networks":[4,15],"requires":[5],"running":[6],"all":[7,55],"the":[8,46,57,73,76,100,121,129,136,139,153],"computation":[9],"encrypted":[11,40],"data.":[12],"Unfortunately,":[13],"contain":[16],"a":[17,34,61,89],"large":[18],"number":[19],"of":[20,48,56,75,138],"non-arithmetic":[21,58],"operations,":[22],"such":[23],"as":[24],"ReLU":[25],"activation":[26],"functions":[27],"and":[28,79,108],"max":[29],"pooling":[30],"layers,":[31],"which":[32,95],"incur":[33],"high":[35],"latency":[36],"cost":[37],"in":[38],"their":[39],"form.":[41],"To":[42],"address":[43],"this":[44,85],"issue,":[45],"majority":[47],"private":[49],"methods":[51],"replace":[52],"some":[53],"or":[54],"operations":[59],"with":[60],"polynomial":[62,132],"approximation.":[63],"This":[64],"step":[65],"introduces":[66],"approximation":[67,102,133],"errors":[68],"that":[69,147],"can":[70,149],"substantially":[71],"alter":[72],"output":[74],"network":[78],"decrease":[80],"its":[81],"predictive":[82],"performance.":[83],"In":[84],"paper,":[86],"we":[87],"propose":[88],"Lipschitz-Guided":[90],"Abstraction":[91],"Refinement":[92],"method":[93,105],"(LiGAR),":[94],"provides":[96],"strong":[97],"guarantees":[98],"global":[101],"error.":[103,123],"Our":[104,143],"is":[106],"iterative,":[107],"leverages":[109],"state-of-the-art":[110],"Lipschitz":[111],"constant":[112],"estimation":[113],"techniques":[114],"to":[115,152],"produce":[116],"increasingly":[117],"tighter":[118],"bounds":[119],"worst-case":[122],"At":[124],"each":[125],"iteration,":[126],"LiGAR":[127,148],"designs":[128],"least":[130],"expensive":[131],"by":[134],"solving":[135],"dual":[137],"corresponding":[140],"optimization":[141],"problem.":[142],"preliminary":[144],"experiments":[145],"show":[146],"easily":[150],"converge":[151],"optimum":[154],"medium-sized":[156],"networks.":[158]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
