{"id":"https://openalex.org/W4310902987","doi":"https://doi.org/10.1109/itw54588.2022.9965815","title":"Private Federated Submodel Learning with Sparsification","display_name":"Private Federated Submodel Learning with Sparsification","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4310902987","doi":"https://doi.org/10.1109/itw54588.2022.9965815"},"language":"en","primary_location":{"id":"doi:10.1109/itw54588.2022.9965815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw54588.2022.9965815","pdf_url":null,"source":{"id":"https://openalex.org/S4363606450","display_name":"2022 IEEE Information Theory Workshop (ITW)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Information Theory Workshop (ITW)","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/A5065747216","display_name":"Sajani Vithana","orcid":"https://orcid.org/0000-0002-8408-5317"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sajani Vithana","raw_affiliation_strings":["University of Maryland,Department of Electrical and Computer Engineering,College Park,MD,20742"],"affiliations":[{"raw_affiliation_string":"University of Maryland,Department of Electrical and Computer Engineering,College Park,MD,20742","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021132487","display_name":"\u015eennur Uluku\u015f","orcid":"https://orcid.org/0000-0002-8219-8190"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sennur Ulukus","raw_affiliation_strings":["University of Maryland,Department of Electrical and Computer Engineering,College Park,MD,20742"],"affiliations":[{"raw_affiliation_string":"University of Maryland,Department of Electrical and Computer Engineering,College Park,MD,20742","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065747216"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.0394,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.78663004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"410","last_page":"415"},"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/T10237","display_name":"Cryptography and Data Security","score":0.9995999932289124,"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":0.9908000230789185,"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":0.7169700860977173}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7169700860977173}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw54588.2022.9965815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw54588.2022.9965815","pdf_url":null,"source":{"id":"https://openalex.org/S4363606450","display_name":"2022 IEEE Information Theory Workshop (ITW)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7900000214576721,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W2073346043","https://openalex.org/W2535690855","https://openalex.org/W2593599278","https://openalex.org/W2599749253","https://openalex.org/W2766140019","https://openalex.org/W2767079719","https://openalex.org/W2768218911","https://openalex.org/W2769644379","https://openalex.org/W2804268522","https://openalex.org/W2808769206","https://openalex.org/W2810715221","https://openalex.org/W2888580722","https://openalex.org/W2912213068","https://openalex.org/W2930926105","https://openalex.org/W2946930197","https://openalex.org/W2950321888","https://openalex.org/W2961382438","https://openalex.org/W2962692592","https://openalex.org/W2963456518","https://openalex.org/W2963766684","https://openalex.org/W2963898134","https://openalex.org/W2964162474","https://openalex.org/W2966527647","https://openalex.org/W2967889168","https://openalex.org/W2970408908","https://openalex.org/W2975043678","https://openalex.org/W2982008584","https://openalex.org/W2987738051","https://openalex.org/W2995022099","https://openalex.org/W3003845025","https://openalex.org/W3015640161","https://openalex.org/W3015901293","https://openalex.org/W3021654819","https://openalex.org/W3045590453","https://openalex.org/W3046264682","https://openalex.org/W3079856735","https://openalex.org/W3081181568","https://openalex.org/W3088731039","https://openalex.org/W3093809760","https://openalex.org/W3103245149","https://openalex.org/W3107557773","https://openalex.org/W3129329365","https://openalex.org/W3136902772","https://openalex.org/W3159560790","https://openalex.org/W3171091364","https://openalex.org/W3189221947","https://openalex.org/W3191104470","https://openalex.org/W3196370796","https://openalex.org/W3198450688","https://openalex.org/W3210888078","https://openalex.org/W4205173135","https://openalex.org/W4221165679","https://openalex.org/W4289655496","https://openalex.org/W4298221930","https://openalex.org/W4298356561","https://openalex.org/W4318619660","https://openalex.org/W6728757088","https://openalex.org/W6745723224","https://openalex.org/W6746200960","https://openalex.org/W6746720608","https://openalex.org/W6751754709","https://openalex.org/W6752985224","https://openalex.org/W6754341472","https://openalex.org/W6763393573","https://openalex.org/W6764838729","https://openalex.org/W6768511045","https://openalex.org/W6769643572","https://openalex.org/W6773348087","https://openalex.org/W6795487366","https://openalex.org/W6801335092"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"We":[0,109,120],"investigate":[1],"the":[2,33,39,45,57,62,66,71,82,93,97,107,140,145,148,151],"problem":[3],"of":[4,47,68,89,99,106,134,144,150],"private":[5],"read":[6],"update":[7,84],"write":[8],"(PRUW)":[9],"in":[10,79,113],"federated":[11],"submodel":[12,34,59,63,141],"learning":[13,21],"(FSL)":[14],"with":[15,118],"sparsification.":[16,119,172],"In":[17],"FSL,":[18],"a":[19,75,86,122],"machine":[20],"model":[22],"is":[23,36,44,74,169],"divided":[24],"into":[25],"multiple":[26],"submodels,":[27],"where":[28,81],"each":[29],"user":[30],"updates":[31,69,103],"only":[32,85],"that":[35],"relevant":[37],"to":[38,56,70,91,131,154,167],"user\u2019s":[40],"local":[41],"data.":[42],"PRUW":[43,112],"process":[46],"privately":[48,126],"performing":[49],"FSL":[50,114],"by":[51],"reading":[52,162],"from":[53,128],"and":[54,129,163],"writing":[55,164],"required":[58],"without":[60,138,171],"revealing":[61,139],"index":[64],"or":[65,147],"values":[67,143],"databases.":[72,155],"Sparsification":[73],"widely":[76],"used":[77],"concept":[78],"learning,":[80],"users":[83],"small":[87],"fraction":[88],"parameters":[90,133],"reduce":[92],"communication":[94],"cost.":[95],"Revealing":[96],"coordinates":[98,149],"these":[100],"selected":[101],"(sparse)":[102],"leaks":[104],"privacy":[105],"user.":[108],"show":[110],"how":[111],"can":[115],"be":[116],"performed":[117],"propose":[121],"novel":[123],"scheme":[124,158],"which":[125],"reads":[127],"writes":[130],"arbitrary":[132],"any":[135],"given":[136],"submodel,":[137],"index,":[142],"updates,":[146,153],"sparse":[152],"The":[156],"proposed":[157],"achieves":[159],"significantly":[160],"lower":[161],"costs":[165],"compared":[166],"what":[168],"achieved":[170]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}