{"id":"https://openalex.org/W4405909403","doi":"https://doi.org/10.1109/itw61385.2024.10807033","title":"FedUHB: Accelerating Federated Unlearning via Polyak Heavy Ball Method","display_name":"FedUHB: Accelerating Federated Unlearning via Polyak Heavy Ball Method","publication_year":2024,"publication_date":"2024-11-24","ids":{"openalex":"https://openalex.org/W4405909403","doi":"https://doi.org/10.1109/itw61385.2024.10807033"},"language":"en","primary_location":{"id":"doi:10.1109/itw61385.2024.10807033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw61385.2024.10807033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101626154","display_name":"Yu Jiang","orcid":"https://orcid.org/0000-0002-7369-3173"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yu Jiang","raw_affiliation_strings":["Nanyang Technological University Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079559561","display_name":"Chee Wei Tan","orcid":"https://orcid.org/0000-0002-6624-9752"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chee Wei Tan","raw_affiliation_strings":["Nanyang Technological University Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101720092","display_name":"Kwok\u2010Yan Lam","orcid":"https://orcid.org/0000-0001-7479-7970"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kwok-Yan Lam","raw_affiliation_strings":["Nanyang Technological University Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"235","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8334000110626221,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.8334000110626221,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.8033999800682068,"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/T11693","display_name":"Cryptography and Residue Arithmetic","score":0.7915999889373779,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/ball","display_name":"Ball (mathematics)","score":0.723029375076294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.673614501953125},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.35719212889671326},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12302058935165405}],"concepts":[{"id":"https://openalex.org/C122041747","wikidata":"https://www.wikidata.org/wiki/Q838611","display_name":"Ball (mathematics)","level":2,"score":0.723029375076294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.673614501953125},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35719212889671326},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12302058935165405},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itw61385.2024.10807033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itw61385.2024.10807033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Information Theory Workshop (ITW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1988720110","https://openalex.org/W2007339694","https://openalex.org/W2030161963","https://openalex.org/W2137731592","https://openalex.org/W2535690855","https://openalex.org/W2758544228","https://openalex.org/W2763081248","https://openalex.org/W2884283597","https://openalex.org/W3007279825","https://openalex.org/W3021654819","https://openalex.org/W3107337211","https://openalex.org/W3186590963","https://openalex.org/W3197363474","https://openalex.org/W4206320562","https://openalex.org/W4226049484","https://openalex.org/W4244393449","https://openalex.org/W4250589301","https://openalex.org/W4285506551","https://openalex.org/W4292084264","https://openalex.org/W4292363360","https://openalex.org/W4311114086","https://openalex.org/W4312926285","https://openalex.org/W4365790479","https://openalex.org/W4384948739","https://openalex.org/W4385154262","https://openalex.org/W4391019609","https://openalex.org/W4400314239","https://openalex.org/W4400830279","https://openalex.org/W4404701208","https://openalex.org/W6728757088","https://openalex.org/W6811351543","https://openalex.org/W6853968819","https://openalex.org/W6860229034","https://openalex.org/W6862998838"],"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":{"Federated":[0],"learning":[1,185],"facilitates":[2],"collaborative":[3],"machine":[4],"learning,":[5],"enabling":[6],"multiple":[7],"participants":[8],"to":[9,28,35,49,71,84,112,124],"collectively":[10],"develop":[11],"a":[12,96,109,120],"shared":[13],"model":[14,147],"while":[15],"preserving":[16],"the":[17,26,52,58,103,126,129,152,158],"privacy":[18],"of":[19,25,54,128,160],"individual":[20],"data.":[21],"The":[22],"growing":[23],"importance":[24],"\u201cright":[27],"be":[29,171],"forgotten\u201d":[30],"calls":[31],"for":[32,179],"effective":[33,175],"mechanisms":[34],"facilitate":[36],"data":[37,56,73,87,181],"removal":[38,74,182],"upon":[39],"request.":[40],"In":[41,116],"response,":[42],"federated":[43,184],"unlearning":[44,67,99,130,141,161],"(FU)":[45],"has":[46],"been":[47],"developed":[48],"efficiently":[50],"eliminate":[51],"influence":[53],"specific":[55],"from":[57],"model.":[59],"Current":[60],"FU":[61],"methods":[62],"primarily":[63],"rely":[64],"on":[65],"approximate":[66],"strategies,":[68],"which":[69],"seek":[70],"balance":[72],"efficacy":[75],"with":[76],"computational":[77,165],"and":[78,166,176],"communication":[79,167],"costs,":[80],"but":[81,143],"often":[82],"fail":[83],"completely":[85],"erase":[86],"influence.":[88],"To":[89],"address":[90],"these":[91],"limitations,":[92],"we":[93,118],"propose":[94],"FedUHB,":[95],"novel":[97],"exact":[98,180],"approach":[100],"that":[101,136],"leverages":[102],"Polyak":[104],"heavy":[105],"ball":[106],"optimization":[107],"technique,":[108],"first-order":[110],"method,":[111],"achieve":[113],"rapid":[114],"retraining.":[115],"addition,":[117],"introduce":[119],"dynamic":[121,153],"stopping":[122,154],"mechanism":[123,155],"optimize":[125],"termination":[127],"process.":[131],"Our":[132],"extensive":[133],"experiments":[134],"show":[135],"FedUHB":[137,169],"not":[138],"only":[139],"enhances":[140],"efficiency":[142],"also":[144],"preserves":[145],"robust":[146],"performance":[148],"after":[149],"unlearning.":[150],"Furthermore,":[151],"effectively":[156],"reduces":[157],"number":[159],"iterations,":[162],"conserving":[163],"both":[164],"resources.":[168],"can":[170],"proved":[172],"as":[173],"an":[174],"efficient":[177],"solution":[178],"in":[183],"settings.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}