{"id":"https://openalex.org/W4312261078","doi":"https://doi.org/10.1109/icpr56361.2022.9956684","title":"BAFL: Federated Learning with Base Ablation for Cost Effective Communication","display_name":"BAFL: Federated Learning with Base Ablation for Cost Effective Communication","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312261078","doi":"https://doi.org/10.1109/icpr56361.2022.9956684"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956684","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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 26th International Conference on Pattern Recognition (ICPR)","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/A5072327779","display_name":"Mayank Kumar Kundalwal","orcid":"https://orcid.org/0000-0001-9707-1558"},"institutions":[{"id":"https://openalex.org/I154549908","display_name":"Indian Institute of Technology Jodhpur","ror":"https://ror.org/03yacj906","country_code":"IN","type":"education","lineage":["https://openalex.org/I154549908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mayank Kumar Kundalwal","raw_affiliation_strings":["IIT Jodhpur,India","IIT Jodhpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Jodhpur,India","institution_ids":["https://openalex.org/I154549908"]},{"raw_affiliation_string":"IIT Jodhpur, India","institution_ids":["https://openalex.org/I154549908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062954566","display_name":"Anurag Saraswat","orcid":null},"institutions":[{"id":"https://openalex.org/I154549908","display_name":"Indian Institute of Technology Jodhpur","ror":"https://ror.org/03yacj906","country_code":"IN","type":"education","lineage":["https://openalex.org/I154549908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anurag Saraswat","raw_affiliation_strings":["IIT Jodhpur,India","IIT Jodhpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Jodhpur,India","institution_ids":["https://openalex.org/I154549908"]},{"raw_affiliation_string":"IIT Jodhpur, India","institution_ids":["https://openalex.org/I154549908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101558988","display_name":"Ishan Mishra","orcid":"https://orcid.org/0009-0001-6314-5536"},"institutions":[{"id":"https://openalex.org/I154549908","display_name":"Indian Institute of Technology Jodhpur","ror":"https://ror.org/03yacj906","country_code":"IN","type":"education","lineage":["https://openalex.org/I154549908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ishan Mishra","raw_affiliation_strings":["IIT Jodhpur,India","IIT Jodhpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Jodhpur,India","institution_ids":["https://openalex.org/I154549908"]},{"raw_affiliation_string":"IIT Jodhpur, India","institution_ids":["https://openalex.org/I154549908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030974286","display_name":"Deepak Mishra","orcid":"https://orcid.org/0000-0002-4078-9400"},"institutions":[{"id":"https://openalex.org/I154549908","display_name":"Indian Institute of Technology Jodhpur","ror":"https://ror.org/03yacj906","country_code":"IN","type":"education","lineage":["https://openalex.org/I154549908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepak Mishra","raw_affiliation_strings":["IIT Jodhpur,India","IIT Jodhpur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIT Jodhpur,India","institution_ids":["https://openalex.org/I154549908"]},{"raw_affiliation_string":"IIT Jodhpur, India","institution_ids":["https://openalex.org/I154549908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1038,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.32149483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1922","last_page":"1928"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9546999931335449,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9041000008583069,"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":0.8091005682945251},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7787610292434692},{"id":"https://openalex.org/keywords/cost-reduction","display_name":"Cost reduction","score":0.5780258178710938},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5538828372955322},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5272128582000732},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5191382765769958},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.47514820098876953},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.47437745332717896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44881290197372437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44227421283721924},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3628137707710266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8091005682945251},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7787610292434692},{"id":"https://openalex.org/C2778820799","wikidata":"https://www.wikidata.org/wiki/Q3454688","display_name":"Cost reduction","level":2,"score":0.5780258178710938},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5538828372955322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5272128582000732},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5191382765769958},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.47514820098876953},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.47437745332717896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44881290197372437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44227421283721924},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3628137707710266},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956684","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W2053637704","https://openalex.org/W2119144962","https://openalex.org/W2535838896","https://openalex.org/W2752689052","https://openalex.org/W2783522756","https://openalex.org/W2788816110","https://openalex.org/W2900120080","https://openalex.org/W2920095265","https://openalex.org/W2944844562","https://openalex.org/W2946193510","https://openalex.org/W2963460174","https://openalex.org/W2972570881","https://openalex.org/W2982464076","https://openalex.org/W2991391304","https://openalex.org/W3006555759","https://openalex.org/W3007548213","https://openalex.org/W3027682070","https://openalex.org/W3028382483","https://openalex.org/W3038028469","https://openalex.org/W3101073882","https://openalex.org/W3118608800","https://openalex.org/W3129362180","https://openalex.org/W3156310591","https://openalex.org/W3157503981","https://openalex.org/W3178386862","https://openalex.org/W3183916646","https://openalex.org/W3213815372","https://openalex.org/W4238235930","https://openalex.org/W4287720355","https://openalex.org/W4288113443","https://openalex.org/W4288333953","https://openalex.org/W4294106961","https://openalex.org/W4297687186","https://openalex.org/W4297799876","https://openalex.org/W4318619660","https://openalex.org/W6677580257","https://openalex.org/W6728757088","https://openalex.org/W6743821447","https://openalex.org/W6755988804","https://openalex.org/W6756344106","https://openalex.org/W6759226220","https://openalex.org/W6762375199","https://openalex.org/W6762879059","https://openalex.org/W6767676916","https://openalex.org/W6771536673","https://openalex.org/W6773817997","https://openalex.org/W6774195376","https://openalex.org/W6775180186","https://openalex.org/W6778147704","https://openalex.org/W6778180876","https://openalex.org/W6780499206","https://openalex.org/W6780897730","https://openalex.org/W6787972765","https://openalex.org/W6790034021","https://openalex.org/W6791444617","https://openalex.org/W6794251734","https://openalex.org/W6840756468","https://openalex.org/W6842749662"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W183202219","https://openalex.org/W3095877357","https://openalex.org/W2072565696","https://openalex.org/W2050451745","https://openalex.org/W2378903222"],"abstract_inverted_index":{"Federated":[0],"learning":[1,6],"is":[2],"a":[3,12,45,69,104,124,133],"distributed":[4],"machine":[5],"setting":[7],"in":[8,26,53,82,138,202,238,252],"which":[9],"clients":[10,173,192],"train":[11],"global":[13,47,134],"model":[14,31,93,125,190],"on":[15,127,162,179,223],"their":[16,21,180],"local":[17,181],"data":[18,57,131],"and":[19,59,67,142,191,220,228,230,255,258],"share":[20],"knowledge":[22,42],"with":[23],"the":[24,29,36,65,88,98,109,144,151,163,189,197,211,215,245],"server":[25,39],"form":[27],"of":[28,35,91,113,118,204,236],"trained":[30],"while":[32,187],"maintaining":[33],"privacy":[34],"data.":[37,182],"The":[38,172],"aggregates":[40],"clients'":[41],"to":[43,87,96,107,196,233,244],"create":[44],"generalized":[46,152],"model.":[48,135,153],"Two":[49],"major":[50],"challenges":[51],"faced":[52],"this":[54],"process":[55],"are":[56,185],"heterogeneity":[58],"high":[60],"communication":[61,81,100,146,205,240],"cost.":[62],"We":[63,122,154,213,249],"target":[64],"latter":[66],"propose":[68,103],"simple":[70],"approach,":[71],"BAFL":[72],"(Federated":[73],"Learning":[74],"for":[75,78,149,166],"Base":[76,183],"Ablation)":[77],"cost":[79,147,157,206,241],"effective":[80],"federated":[83,247],"learning.":[84,248],"In":[85],"contrast":[86],"common":[89],"practice":[90],"employing":[92],"compression":[94],"techniques":[95],"reduce":[97],"total":[99,145,239],"cost,":[101],"we":[102],"fine-tuning":[105],"approach":[106,217],"leverage":[108],"feature":[110],"extraction":[111],"ability":[112],"layers":[114,164,178,184],"at":[115],"different":[116],"depths":[117],"deep":[119],"neural":[120],"networks.":[121],"use":[123],"pretrained":[126],"general-purpose":[128],"large":[129],"scale":[130],"as":[132,242],"This":[136,200],"helps":[137],"better":[139],"weight":[140],"initialization":[141],"reduces":[143],"required":[148],"obtaining":[150],"achieve":[155],"further":[156],"reduction":[158,203,237],"by":[159],"focusing":[160],"only":[161,176],"responsible":[165],"semantic":[167],"features":[168],"(data":[169],"specific":[170],"information).":[171],"fine":[174],"tune":[175],"top":[177],"ablated":[186],"transferring":[188],"communicate":[193],"parameters":[194],"corresponding":[195],"remaining":[198],"layers.":[199],"results":[201],"per":[207],"round":[208],"without":[209],"compromising":[210],"accuracy.":[212],"evaluate":[214],"proposed":[216],"using":[218],"VGG-16":[219],"ResNet-50":[221],"models":[222],"datasets":[224],"including":[225],"WBC,":[226],"FOOD-101,":[227],"CIFAR-10":[229],"obtain":[231],"up":[232],"two":[234],"orders":[235],"compared":[243],"conventional":[246],"perform":[250],"experiments":[251],"both":[253],"IID":[254],"Non-IID":[256],"settings":[257],"observe":[259],"consistent":[260],"improvements.":[261]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}