{"id":"https://openalex.org/W7214134674","doi":null,"title":"Exploring Utility-Fairness-Privacy Trade-offs in Synthetic Sensitive Tabular Data","display_name":"Exploring Utility-Fairness-Privacy Trade-offs in Synthetic Sensitive Tabular Data","publication_year":2026,"publication_date":"2026-11-23","ids":{"openalex":"https://openalex.org/W7214134674"},"language":"en","primary_location":{"id":"pmh:oai:HAL:hal-05741386v1","doi":null,"is_oa":true,"landing_page_url":"https://hal.science/hal-05741386v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Neural Information Processing, Nov 2026, Melbourne, Australia","raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-05741386v1","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119833162","display_name":"Malek Adouani","orcid":"https://orcid.org/0009-0003-8639-7968","observed_orcids":["https://orcid.org/0009-0003-8639-7968"]},"institutions":[{"id":"https://openalex.org/I195731000","display_name":"Universit\u00e9 de Versailles Saint-Quentin-en-Yvelines","ror":"https://ror.org/03mkjjy25","country_code":"FR","type":"education","lineage":["https://openalex.org/I195731000","https://openalex.org/I277688954"]},{"id":"https://openalex.org/I4390039268","display_name":"Donn\u00e9es et algorithmes pour une ville intelligente et durable","ror":"https://ror.org/01xta2p78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I195731000","https://openalex.org/I277688954","https://openalex.org/I4390039268"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Adouani, Malek","raw_affiliation_strings":["DAVID - Donn\u00e9es et algorithmes pour une ville intelligente et durable - DAVID (B\u00e2timent Descartes \u2014 Campus des SciencesUniversit\u00e9 de Versailles Saint-Quentin45 avenue des \u00c9tats-Unis78035 Versailles - France)","UVSQ - Universit\u00e9 de Versailles Saint-Quentin-en-Yvelines (55 avenue de Paris - 78035 Versailles cedex - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAVID - Donn\u00e9es et algorithmes pour une ville intelligente et durable - DAVID (B\u00e2timent Descartes \u2014 Campus des SciencesUniversit\u00e9 de Versailles Saint-Quentin45 avenue des \u00c9tats-Unis78035 Versailles - France)","institution_ids":["https://openalex.org/I195731000","https://openalex.org/I4390039268"]},{"raw_affiliation_string":"UVSQ - Universit\u00e9 de Versailles Saint-Quentin-en-Yvelines (55 avenue de Paris - 78035 Versailles cedex - France)","institution_ids":["https://openalex.org/I195731000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018448962","display_name":"Zaineb Chelly Dagdia","orcid":"https://orcid.org/0000-0002-2551-6586","observed_orcids":["https://orcid.org/0000-0002-2551-6586"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chelly Dagdia, Zaineb","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9916999936103821,"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":0.9916999936103821,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.0005000000237487257,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.00039999998989515007,"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/synthetic-tabular-data-generation","display_name":"synthetic tabular data generation","score":0.7990000247955322},{"id":"https://openalex.org/keywords/pareto-front","display_name":"Pareto front","score":0.7210000157356262},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"multi-objective optimization","score":0.7590000033378601},{"id":"https://openalex.org/keywords/nsga-ii","display_name":"NSGA-II","score":0.8489999771118164},{"id":"https://openalex.org/keywords/evolutionary-search","display_name":"evolutionary search","score":0.5350000262260437},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"simulated annealing","score":0.6980000138282776},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.9829999804496765},{"id":"https://openalex.org/keywords/data-privacy","display_name":"data privacy","score":0.3540000021457672},{"id":"https://openalex.org/keywords/demographic-fairness","display_name":"demographic fairness","score":0.7620000243186951},{"id":"https://openalex.org/keywords/data-utility","display_name":"data utility","score":0.3059999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5498999953269958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.27799999713897705},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25040000677108765},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2433999925851822},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.24310000240802765},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.24130000174045563}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:HAL:hal-05741386v1","doi":null,"is_oa":true,"landing_page_url":"https://hal.science/hal-05741386v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Neural Information Processing, Nov 2026, Melbourne, Australia","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-05741386v1","doi":null,"is_oa":true,"landing_page_url":"https://hal.science/hal-05741386v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Neural Information Processing, Nov 2026, Melbourne, Australia","raw_type":"info:eu-repo/semantics/conferenceObject"},"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/W7214141325","https://openalex.org/W4411255619","https://openalex.org/W7131667498","https://openalex.org/W4414645413","https://openalex.org/W7213226566","https://openalex.org/W4414789742","https://openalex.org/W4409746746","https://openalex.org/W4403882772","https://openalex.org/W7165153957","https://openalex.org/W7167620694"],"abstract_inverted_index":{"Sharing":[0],"sensitive":[1],"tabular":[2],"healthcare":[3,108],"data":[4,169],"requires":[5],"generative":[6,55,151],"models":[7],"that":[8,118,143],"balance":[9],"the":[10,44,72,163],"fundamentally":[11],"conflicting":[12],"objectives":[13],"of":[14],"statistical":[15],"utility,":[16],"demographic":[17],"fairness,":[18],"and":[19,37,65,90],"individual":[20],"privacy.":[21],"Conventional":[22],"configuration":[23,57,146],"relies":[24],"on":[25],"scalarized":[26,94,119],"search,":[27],"which":[28],"reduces":[29],"this":[30],"multidimensional":[31],"tension":[32],"to":[33,70,97,138],"a":[34,39,52,59,77,83,144,158],"single":[35,40,145],"score":[36],"returns":[38],"operating":[41],"point,":[42],"leaving":[43],"broader":[45],"trade-off":[46,165],"landscape":[47,84,166],"unexplored.":[48],"We":[49],"introduce":[50],"Evo-Clust-VAE-WGAN-GP,":[51],"framework":[53,160],"treating":[54],"model":[56,152],"as":[58,93,157],"tri-objective":[60],"optimization":[61],"problem":[62],"over":[63],"structural":[64],"training":[66],"hyperparameters":[67],"using":[68,87],"NSGA-II":[69],"approximate":[71],"Pareto":[73,133],"front.":[74],"Rather":[75],"than":[76],"head-to-head":[78],"optimizer":[79],"contest,":[80],"we":[81],"conduct":[82],"characterization":[85],"study,":[86],"Simulated":[88],"Annealing":[89],"Bayesian":[91],"Optimization":[92],"reference":[95],"probes":[96,120],"expose":[98],"what":[99],"single-point":[100],"strategies":[101],"structurally":[102],"cannot":[103,148],"access.":[104],"Evaluating":[105],"across":[106],"five":[107],"benchmarks":[109],"(HIV,":[110],"Stress,":[111],"Obesity,":[112],"Heart":[113],"Failure,":[114],"Pediatric),":[115],"results":[116],"show":[117],"consistently":[121],"collapse":[122],"onto":[123],"dataset-insensitive":[124],"regions.":[125],"In":[126],"contrast,":[127],"evolutionary":[128],"search":[129,156],"uncovers":[130],"well-distributed,":[131],"dataset-dependent":[132],"fronts":[134],"ranging":[135],"from":[136],"continuous":[137],"fragmented.":[139],"These":[140],"findings":[141],"demonstrate":[142],"compromise":[147],"adequately":[149],"represent":[150],"behavior,":[153],"establishing":[154],"population-based":[155],"principled":[159],"for":[161],"exposing":[162],"full":[164],"in":[167],"privacy-sensitive":[168],"generation.":[170]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-09-24T00:00:00"}
