{"id":"https://openalex.org/W4399332405","doi":"https://doi.org/10.1145/3655693.3660253","title":"Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training","display_name":"Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training","publication_year":2024,"publication_date":"2024-06-04","ids":{"openalex":"https://openalex.org/W4399332405","doi":"https://doi.org/10.1145/3655693.3660253"},"language":"en","primary_location":{"id":"doi:10.1145/3655693.3660253","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3655693.3660253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"European Interdisciplinary Cybersecurity Conference","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/A5035735692","display_name":"Dmitrii Usynin","orcid":"https://orcid.org/0000-0003-0179-6138"},"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"]},{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["DE","GB"],"is_corresponding":true,"raw_author_name":"Dmitrii Usynin","raw_affiliation_strings":["Imperial College London, United Kingdom and Technical University of Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom and Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508","https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006461848","display_name":"Daniel Rueckert","orcid":"https://orcid.org/0000-0002-5683-5889"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]},{"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","GB"],"is_corresponding":false,"raw_author_name":"Daniel Rueckert","raw_affiliation_strings":["Imperial College London, United Kingdom and Technical University of Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Imperial College London, United Kingdom and Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508","https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000554104","display_name":"Georgios Kaissis","orcid":"https://orcid.org/0000-0001-8382-8062"},"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":"Georgios Kaissis","raw_affiliation_strings":["Technical University of Munich, Germany and Institute for Machine Learning in Biomedical Imaging, Helmholtz AI, Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany and Institute for Machine Learning in Biomedical Imaging, Helmholtz AI, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5035735692"],"corresponding_institution_ids":["https://openalex.org/I47508984","https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06065936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"179","last_page":"185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9750000238418579,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.9717000126838684,"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/computer-science","display_name":"Computer science","score":0.7544327974319458},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7081218957901001},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6607564091682434},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5860560536384583},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.5061132311820984},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5057997703552246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47790345549583435},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4675867557525635},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.44400957226753235},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.42304202914237976},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4128338694572449},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.4103277325630188},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.17514640092849731},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.15376484394073486},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.11650216579437256},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.09900757670402527}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7544327974319458},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7081218957901001},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6607564091682434},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5860560536384583},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.5061132311820984},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5057997703552246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47790345549583435},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4675867557525635},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.44400957226753235},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.42304202914237976},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4128338694572449},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.4103277325630188},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.17514640092849731},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15376484394073486},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.11650216579437256},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09900757670402527},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3655693.3660253","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3655693.3660253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"European Interdisciplinary Cybersecurity Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:push-zb.helmholtz-munich.de:70896","is_oa":false,"landing_page_url":"https://push-zb.helmholtz-munich.de/frontdoor.php?source_opus=70896","pdf_url":null,"source":{"id":"https://openalex.org/S7407055352","display_name":"PuSH - Publication Server of Helmholtz Zentrum M\u00fcnchen","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In:. 2024. 179-185 (ACM International Conference Proceeding Series)","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2133665775","https://openalex.org/W2149197198","https://openalex.org/W2473418344","https://openalex.org/W3035261884","https://openalex.org/W3035616549","https://openalex.org/W3037261120","https://openalex.org/W3080234712","https://openalex.org/W3080532707","https://openalex.org/W3094874121","https://openalex.org/W3116863821","https://openalex.org/W3126228234","https://openalex.org/W3154335119","https://openalex.org/W3165750456","https://openalex.org/W3172995810","https://openalex.org/W3184865800","https://openalex.org/W3187308167","https://openalex.org/W3200636593","https://openalex.org/W3212504668","https://openalex.org/W4205228770","https://openalex.org/W4280512093","https://openalex.org/W6797075700"],"related_works":["https://openalex.org/W4298221930","https://openalex.org/W3081133439","https://openalex.org/W4386246791","https://openalex.org/W2945537679","https://openalex.org/W4388282301","https://openalex.org/W3211701140","https://openalex.org/W2952280724","https://openalex.org/W2133103607","https://openalex.org/W4285322112","https://openalex.org/W4292794239"],"abstract_inverted_index":{"Obtaining":[0],"high-quality":[1],"data":[2,25,74,92,110,140,179],"for":[3,70,143,177],"collaborative":[4],"training":[5,80,135],"of":[6,24,39,84,133,155],"machine":[7,41],"learning":[8,42],"models":[9],"can":[10,33,63,99,170],"be":[11,34,64],"a":[12,22],"challenging":[13],"task":[14],"due":[15],"to":[16,28,73,78,115,125,129,137],"A)":[17],"regulatory":[18],"concerns":[19],"and":[20,47,104,158],"B)":[21],"lack":[23],"owner":[26],"incentives":[27],"participate.":[29],"The":[30,60],"first":[31],"issue":[32],"addressed":[35,65],"through":[36],"the":[37,54,68,79,91,102,105,131,139,144,159,172],"combination":[38],"distributed":[40],"techniques":[43,169],"(e.g.":[44],"federated":[45,88,173],"learning)":[46],"privacy":[48,160,184],"enhancing":[49],"technologies":[50],"(PET),":[51],"such":[52,151],"as":[53],"differentially":[55],"private":[56,134],"(DP)":[57],"model":[58],"training.":[59],"second":[61],"challenge":[62],"by":[66],"rewarding":[67],"participants":[69,132],"giving":[71],"access":[72],"which":[75,82],"is":[76,83,93],"beneficial":[77,142],"model,":[81],"particular":[85],"importance":[86],"in":[87,182],"settings,":[89],"where":[90],"unevenly":[94],"distributed.":[95],"However,":[96],"DP":[97],"noise":[98],"adversely":[100],"affect":[101],"underrepresented":[103],"atypical":[106],"(yet":[107],"often":[108],"informative)":[109],"samples,":[111],"making":[112],"it":[113],"difficult":[114],"assess":[116,149],"their":[117],"usefulness.":[118],"In":[119],"this":[120],"work,":[121],"we":[122],"investigate":[123],"how":[124],"leverage":[126],"gradient":[127],"information":[128],"permit":[130],"settings":[136],"select":[138],"most":[141],"jointly":[145],"trained":[146],"model.":[147],"We":[148,165],"two":[150],"methods,":[152],"namely":[153],"variance":[154],"gradients":[156],"(VoG)":[157],"loss-input":[161],"susceptibility":[162],"score":[163],"(PLIS).":[164],"show":[166],"that":[167],"these":[168],"provide":[171],"clients":[174],"with":[175],"tools":[176],"principled":[178],"selection":[180],"even":[181],"stricter":[183],"settings.":[185]},"counts_by_year":[],"updated_date":"2026-03-02T08:37:19.008085","created_date":"2025-10-10T00:00:00"}
