{"id":"https://openalex.org/W4367000294","doi":"https://doi.org/10.48550/arxiv.2304.12117","title":"FedPIDAvg: A PID controller inspired aggregation method for Federated Learning","display_name":"FedPIDAvg: A PID controller inspired aggregation method for Federated Learning","publication_year":2023,"publication_date":"2023-04-24","ids":{"openalex":"https://openalex.org/W4367000294","doi":"https://doi.org/10.48550/arxiv.2304.12117"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2304.12117","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.12117","pdf_url":"https://arxiv.org/pdf/2304.12117","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2304.12117","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036005754","display_name":"Leon M\u00e4chler","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M\u00e4chler, Leon","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039935645","display_name":"Ivan Ezhov","orcid":"https://orcid.org/0000-0002-0862-6513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ezhov, Ivan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018632773","display_name":"Suprosanna Shit","orcid":"https://orcid.org/0000-0003-4435-7207"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shit, Suprosanna","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085027983","display_name":"Johannes C. Paetzold","orcid":"https://orcid.org/0000-0002-4844-6955"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paetzold, Johannes C.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036005754"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"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/T10862","display_name":"AI in cancer detection","score":0.9987999796867371,"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/T10862","display_name":"AI in cancer detection","score":0.9987999796867371,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.993399977684021,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pid-controller","display_name":"PID controller","score":0.8251224756240845},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6618276834487915},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.572822630405426},{"id":"https://openalex.org/keywords/controller","display_name":"Controller (irrigation)","score":0.5528664588928223},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4696701467037201},{"id":"https://openalex.org/keywords/derivative","display_name":"Derivative (finance)","score":0.44018369913101196},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37096482515335083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1719495952129364},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14644008874893188},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.14201399683952332},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11004117131233215},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.10090047121047974}],"concepts":[{"id":"https://openalex.org/C47116090","wikidata":"https://www.wikidata.org/wiki/Q716829","display_name":"PID controller","level":3,"score":0.8251224756240845},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6618276834487915},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.572822630405426},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.5528664588928223},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4696701467037201},{"id":"https://openalex.org/C111771559","wikidata":"https://www.wikidata.org/wiki/Q66295","display_name":"Derivative (finance)","level":2,"score":0.44018369913101196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37096482515335083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1719495952129364},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14644008874893188},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.14201399683952332},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11004117131233215},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.10090047121047974},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C536315585","wikidata":"https://www.wikidata.org/wiki/Q7698332","display_name":"Temperature control","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2304.12117","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.12117","pdf_url":"https://arxiv.org/pdf/2304.12117","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2304.12117","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2304.12117","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2304.12117","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2304.12117","pdf_url":"https://arxiv.org/pdf/2304.12117","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4367000294.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2002388147","https://openalex.org/W3098928304","https://openalex.org/W2394883510","https://openalex.org/W2150958483","https://openalex.org/W2922503265","https://openalex.org/W2023324176","https://openalex.org/W2121097709","https://openalex.org/W3097920840","https://openalex.org/W2165013373","https://openalex.org/W3212795132"],"abstract_inverted_index":{"This":[0,69],"paper":[1],"presents":[2],"FedPIDAvg,":[3,84],"the":[4,8,44,54,57,60,65,74,88,96,110,121],"winning":[5,19],"submission":[6],"to":[7,21],"Federated":[9],"Tumor":[10],"Segmentation":[11],"Challenge":[12],"2022":[13],"(FETS22).":[14],"Inspired":[15],"by":[16,108],"FedCostWAvg,":[17],"our":[18],"contribution":[20],"FETS21,":[22],"we":[23,85],"contribute":[24],"an":[25],"improved":[26],"aggregation":[27],"strategy":[28],"for":[29],"federated":[30,67],"and":[31,119],"collaborative":[32],"learning.":[33],"FedCostWAvg":[34],"is":[35],"a":[36,78,116],"weighted":[37],"averaging":[38],"method":[39,128],"that":[40],"not":[41],"only":[42],"considers":[43],"number":[45],"of":[46,49,56,59,77,100],"training":[47,122],"samples":[48,102],"each":[50],"cluster":[51],"but":[52],"also":[53],"size":[55,99],"drop":[58],"respective":[61],"cost":[62],"function":[63],"in":[64],"last":[66],"round.":[68],"can":[70],"be":[71],"interpreted":[72],"as":[73,114],"derivative":[75],"part":[76],"PID":[79],"controller":[80],"(proportional-integral-derivative":[81],"controller).":[82],"In":[83],"further":[86],"add":[87],"missing":[89],"integral":[90],"term.":[91],"Another":[92],"key":[93],"challenge":[94],"was":[95],"vastly":[97],"varying":[98],"data":[101,111],"per":[103,124],"center.":[104],"We":[105],"addressed":[106],"this":[107],"modeling":[109],"center":[112,125],"sizes":[113],"following":[115],"Poisson":[117],"distribution":[118],"choosing":[120],"iterations":[123],"accordingly.":[126],"Our":[127],"outperformed":[129],"all":[130],"other":[131],"submissions.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2023-04-27T00:00:00"}