{"id":"https://openalex.org/W4401408778","doi":"https://doi.org/10.1145/3673038.3673074","title":"ChronusFed: Reinforcement-Based Adaptive Partial Training for Heterogeneous Federated Learning","display_name":"ChronusFed: Reinforcement-Based Adaptive Partial Training for Heterogeneous Federated Learning","publication_year":2024,"publication_date":"2024-08-08","ids":{"openalex":"https://openalex.org/W4401408778","doi":"https://doi.org/10.1145/3673038.3673074"},"language":"en","primary_location":{"id":"doi:10.1145/3673038.3673074","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673074","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3673038.3673074","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3673038.3673074","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113325238","display_name":"Fuyuan Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fuyuan Xia","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030888658","display_name":"Chenhao Ying","orcid":"https://orcid.org/0000-0002-2152-3826"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhao Ying","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101435519","display_name":"David S. L. Wei","orcid":"https://orcid.org/0000-0002-3839-5576"},"institutions":[{"id":"https://openalex.org/I164389053","display_name":"Fordham University","ror":"https://ror.org/03qnxaf80","country_code":"US","type":"education","lineage":["https://openalex.org/I164389053"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David S.L. Wei","raw_affiliation_strings":["Fordham University, United States of America"],"affiliations":[{"raw_affiliation_string":"Fordham University, United States of America","institution_ids":["https://openalex.org/I164389053"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106603205","display_name":"Wei Chen","orcid":"https://orcid.org/0009-0006-6328-2510"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076675337","display_name":"Weiting Zhang","orcid":"https://orcid.org/0000-0003-2626-4883"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiting Zhang","raw_affiliation_strings":["Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101778761","display_name":"Haiming Jin","orcid":"https://orcid.org/0000-0001-5178-7198"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiming Jin","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101495751","display_name":"Yuan Luo","orcid":"https://orcid.org/0000-0002-5741-0567"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Luo","raw_affiliation_strings":["Shanghai Jiao Tong University, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5113325238"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65376862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"464","last_page":"473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998000264167786,"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":0.9998000264167786,"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/T13553","display_name":"Age of Information Optimization","score":0.9796000123023987,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.824664831161499},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7765463590621948},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5640241503715515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3642619550228119}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.824664831161499},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7765463590621948},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5640241503715515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3642619550228119},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3673038.3673074","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673074","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3673038.3673074","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3673038.3673074","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3673038.3673074","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3673038.3673074","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 53rd International Conference on Parallel Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401408778.pdf"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2900182564","https://openalex.org/W3008115128","https://openalex.org/W3047304572","https://openalex.org/W3134509799","https://openalex.org/W3190772738","https://openalex.org/W4226167551","https://openalex.org/W4287322665","https://openalex.org/W4289546285","https://openalex.org/W4319663761","https://openalex.org/W4320067864","https://openalex.org/W4320067912","https://openalex.org/W4381785874","https://openalex.org/W4382463479","https://openalex.org/W4385768240","https://openalex.org/W4386869660","https://openalex.org/W4388286154","https://openalex.org/W4390097772","https://openalex.org/W4390873050"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4306904969","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659","https://openalex.org/W258997015"],"abstract_inverted_index":{"Due":[0],"to":[1,37,51,97,133,156],"the":[2,42,52,63,110,122,135,139,170],"progress":[3],"in":[4,17,193],"computer":[5],"hardware":[6,117],"and":[7,54,69,90,105,142,160,174,191],"network":[8],"technologies,":[9],"federated":[10],"learning":[11,131,186],"(FL),":[12],"a":[13,72,84,91],"decentralized":[14],"training":[15,35,76,94,100,146,167],"method":[16,77],"machine":[18],"learning,":[19],"has":[20],"garnered":[21],"widespread":[22],"attention.":[23],"In":[24,58],"this":[25,59],"approach,":[26],"individuals":[27],"share":[28],"local":[29,145],"model":[30,99,123,134,141,162],"parameters":[31],"rather":[32],"than":[33],"raw":[34],"data":[36],"protect":[38],"their":[39],"privacy.":[40],"However,":[41],"inherent":[43],"heterogeneity":[44,159],"of":[45,56,65,138,166,172],"practical":[46],"computing":[47],"devices":[48],"poses":[49],"challenges":[50],"efficiency":[53],"performance":[55],"FL.":[57],"paper,":[60],"we":[61],"explore":[62],"landscape":[64],"heterogeneous":[66,79,194],"FL":[67,195],"frameworks":[68],"introduce":[70],"ChronusFed,":[71,173],"reinforCement-based":[73],"adaptive":[74],"partial":[75,93],"for":[78],"Federated":[80],"learning.":[81],"ChronusFed":[82,107,180],"employs":[83],"dynamic":[85],"epoch":[86],"adjustment":[87],"mechanism":[88],"(DEA)":[89],"customizable":[92],"framework":[95],"(CPT)":[96],"optimize":[98],"efficiency.":[101],"By":[102],"integrating":[103],"DEA":[104,127],"CPT,":[106],"effectively":[108],"tackles":[109],"straggler":[111],"issues":[112],"that":[113,179],"arise":[114],"from":[115],"limited":[116],"resources,":[118],"while":[119,148],"simultaneously":[120],"enhancing":[121],"performance.":[124],"More":[125],"specifically,":[126],"leverages":[128],"deep":[129],"reinforcement":[130],"(DRL)":[132],"current":[136],"state":[137],"global":[140],"determine":[143],"optimal":[144],"epochs,":[147],"CPT":[149],"utilizes":[150],"our":[151],"proposed":[152],"maximum":[153],"coverage":[154],"algorithm":[155],"handle":[157],"device":[158],"accelerate":[161],"convergence.":[163],"Theoretical":[164],"analysis":[165],"convergence":[168],"validates":[169],"effectiveness":[171],"comprehensive":[175],"experimental":[176],"evaluations":[177],"demonstrate":[178],"outperforms":[181],"state-of-the-art":[182],"methods":[183],"across":[184],"various":[185],"tasks,":[187],"showcasing":[188],"its":[189],"robustness":[190],"superiority":[192],"scenarios.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}