{"id":"https://openalex.org/W4392384795","doi":"https://doi.org/10.1145/3616855.3635761","title":"ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees","display_name":"ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees","publication_year":2024,"publication_date":"2024-03-04","ids":{"openalex":"https://openalex.org/W4392384795","doi":"https://doi.org/10.1145/3616855.3635761"},"language":"en","primary_location":{"id":"doi:10.1145/3616855.3635761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616855.3635761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/207608","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079136122","display_name":"Sina Sajadmanesh","orcid":"https://orcid.org/0000-0002-8834-0338"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]},{"id":"https://openalex.org/I7495430","display_name":"Idiap Research Institute","ror":"https://ror.org/05932h694","country_code":"CH","type":"facility","lineage":["https://openalex.org/I7495430"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Sina Sajadmanesh","raw_affiliation_strings":["Idiap Research Institute &amp; EPFL, Martigny, Switzerland"],"raw_orcid":"https://orcid.org/0000-0002-8834-0338","affiliations":[{"raw_affiliation_string":"Idiap Research Institute &amp; EPFL, Martigny, Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I7495430"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012965551","display_name":"Daniel G\u00e1tica-P\u00e9rez","orcid":"https://orcid.org/0000-0001-5488-2182"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]},{"id":"https://openalex.org/I7495430","display_name":"Idiap Research Institute","ror":"https://ror.org/05932h694","country_code":"CH","type":"facility","lineage":["https://openalex.org/I7495430"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Daniel Gatica-Perez","raw_affiliation_strings":["Idiap Research Institute &amp; EPFL, Martigny, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-5488-2182","affiliations":[{"raw_affiliation_string":"Idiap Research Institute &amp; EPFL, Martigny, Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I7495430"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"596","last_page":"605"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9890999794006348,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9560999870300293,"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":0.889555811882019},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8513145446777344},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6180647611618042},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5361393094062805},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5267578959465027},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4997241497039795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45441824197769165},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4428873360157013},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.44238266348838806},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4229137599468231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4008723497390747},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.21141952276229858},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2081294059753418}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.889555811882019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8513145446777344},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6180647611618042},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5361393094062805},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5267578959465027},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4997241497039795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45441824197769165},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4428873360157013},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.44238266348838806},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4229137599468231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4008723497390747},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.21141952276229858},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2081294059753418},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3616855.3635761","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616855.3635761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.epfl.ch:310758","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/207608","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WoS","raw_type":"conference proceedings"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:310758","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/207608","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"WoS","raw_type":"conference proceedings"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1322071649","display_name":"A European Excellence Centre for Media, Society and Democracy","funder_award_id":"951911","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G2017605187","display_name":null,"funder_award_id":"H2020 Program","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G3509845443","display_name":null,"funder_award_id":"951911","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G3542563520","display_name":null,"funder_award_id":"ICT-48-2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G4397263494","display_name":null,"funder_award_id":"951911","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G4937468798","display_name":null,"funder_award_id":"H2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5871011076","display_name":null,"funder_award_id":"ICT-48-2020","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G7474279210","display_name":"WeNet - The Internet of US","funder_award_id":"823783","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G8107045763","display_name":null,"funder_award_id":"823783","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2245160765","https://openalex.org/W2473418344","https://openalex.org/W2801995427","https://openalex.org/W2807021761","https://openalex.org/W2809583854","https://openalex.org/W2912083425","https://openalex.org/W2945827377","https://openalex.org/W2963757395","https://openalex.org/W2964042923","https://openalex.org/W3035575271","https://openalex.org/W3100848837","https://openalex.org/W3101553402","https://openalex.org/W3123909522","https://openalex.org/W3125963848","https://openalex.org/W3137188301","https://openalex.org/W3154109599","https://openalex.org/W3186133345","https://openalex.org/W3196012972","https://openalex.org/W3214714397","https://openalex.org/W4212774754","https://openalex.org/W4226159313","https://openalex.org/W4308613145","https://openalex.org/W4308641868","https://openalex.org/W4312521712","https://openalex.org/W6600586173","https://openalex.org/W6748856961"],"related_works":["https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2558166297","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2964481303","https://openalex.org/W1751413323","https://openalex.org/W2571704763","https://openalex.org/W4315488958"],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4,33],"become":[5],"a":[6,75,84,105,108],"popular":[7],"tool":[8],"for":[9,43,171],"learning":[10,45],"on":[11,181],"graphs,":[12],"but":[13],"their":[14],"widespread":[15],"use":[16],"raises":[17],"privacy":[18,39,57,158,169],"concerns":[19],"as":[20],"graph":[21,183],"data":[22],"can":[23,190],"contain":[24],"personal":[25],"or":[26],"sensitive":[27],"information.":[28],"Differentially":[29],"private":[30,78,201],"GNN":[31,79,106],"models":[32],"been":[34],"recently":[35],"proposed":[36],"to":[37,63,88,99,122,145,151,193],"preserve":[38],"while":[40,154],"still":[41],"allowing":[42],"effective":[44],"over":[46,131],"graph-structured":[47],"datasets.":[48,184],"However,":[49],"achieving":[50],"an":[51,146],"ideal":[52],"balance":[53],"between":[54],"accuracy":[55,196],"and":[56,138,167,174,177],"in":[58],"GNNs":[59],"remains":[60],"challenging":[61],"due":[62],"the":[64,95,119,123,132,141,156],"intrinsic":[65],"structural":[66],"connectivity":[67],"of":[68,110],"graphs.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"propose":[74],"new":[76],"differentially":[77,200],"called":[80],"ProGAP":[81,103,164,189],"that":[82,113,163,188],"uses":[83],"progressive":[85],"training":[86,173],"scheme":[87],"improve":[89],"such":[90],"accuracy-privacy":[91],"trade-offs.":[92],"Combined":[93],"with":[94],"aggregation":[96],"perturbation":[97],"technique":[98],"ensure":[100],"differential":[101],"privacy,":[102],"splits":[104],"into":[107],"sequence":[109],"overlapping":[111],"submodels":[112],"are":[114],"trained":[115,130],"progressively,":[116],"expanding":[117],"from":[118],"first":[120],"submodel":[121,128],"complete":[124],"model.":[125],"Specifically,":[126],"each":[127],"is":[129,205],"privately":[133],"aggregated":[134],"node":[135],"embeddings":[136],"learned":[137],"cached":[139],"by":[140],"previous":[142,152],"submodels,":[143],"leading":[144],"increased":[147],"expressive":[148],"power":[149],"compared":[150],"approaches":[153],"limiting":[155],"incurred":[157],"costs.":[159],"We":[160],"formally":[161],"prove":[162],"ensures":[165],"edge-level":[166],"node-level":[168],"guarantees":[170],"both":[172],"inference":[175],"stages,":[176],"evaluate":[178],"its":[179],"performance":[180],"benchmark":[182],"Experimental":[185],"results":[186],"demonstrate":[187],"achieve":[191],"up":[192],"5-10%":[194],"higher":[195],"than":[197],"existing":[198],"state-of-the-art":[199],"GNNs.":[202],"Our":[203],"code":[204],"available":[206],"at":[207],"https://github.com/sisaman/ProGAP.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
