{"id":"https://openalex.org/W4406458304","doi":"https://doi.org/10.1109/bigdata62323.2024.10825613","title":"Federated Multi-task Learning in Distributed Networks","display_name":"Federated Multi-task Learning in Distributed Networks","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458304","doi":"https://doi.org/10.1109/bigdata62323.2024.10825613"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5091633816","display_name":"Lingzhou Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lingzhou Hong","raw_affiliation_strings":["Texas A&M University,Department of Industrial & Systems Engineering,College Station,USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University,Department of Industrial & Systems Engineering,College Station,USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018111786","display_name":"Alfredo Garc\u00eda","orcid":null},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alfredo Garcia","raw_affiliation_strings":["Texas A&M University,Department of Industrial & Systems Engineering,College Station,USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University,Department of Industrial & Systems Engineering,College Station,USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5091633816"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23050563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7800","last_page":"7809"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9965000152587891,"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/T12676","display_name":"Machine Learning and ELM","score":0.9958999752998352,"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":0.7790601253509521},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6821402311325073},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.41191989183425903},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3975973427295685},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.08362740278244019},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06734836101531982}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7790601253509521},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6821402311325073},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.41191989183425903},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3975973427295685},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.08362740278244019},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06734836101531982}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825613","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825613","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W216325278","https://openalex.org/W338925043","https://openalex.org/W1625972580","https://openalex.org/W2097451239","https://openalex.org/W2383193739","https://openalex.org/W2562969225","https://openalex.org/W2972087877","https://openalex.org/W3012125688","https://openalex.org/W3012220622","https://openalex.org/W3086809868","https://openalex.org/W3087549734","https://openalex.org/W3092482340","https://openalex.org/W3118706837","https://openalex.org/W3124818701","https://openalex.org/W3141797743","https://openalex.org/W4205941233","https://openalex.org/W4300427714","https://openalex.org/W4403916486","https://openalex.org/W6689726706","https://openalex.org/W6738383168","https://openalex.org/W6775649616","https://openalex.org/W6783292247","https://openalex.org/W6874594730"],"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/W2951720331"],"abstract_inverted_index":{"We":[0,22,72],"consider":[1],"a":[2,40,47,74],"Distributed":[3],"Federated":[4],"multitask":[5],"learning":[6,34],"scheme":[7],"that":[8,24],"accounts":[9],"for":[10],"multiple":[11],"linear":[12,48],"model":[13,49],"estimation":[14],"tasks":[15,35],"with":[16],"heterogeneous":[17],"and/or":[18],"correlated":[19],"data":[20],"streams.":[21],"assume":[23],"nodes":[25],"can":[26],"be":[27],"partitioned":[28],"into":[29],"groups":[30],"corresponding":[31],"to":[32,39,54],"different":[33],"and":[36,51,58,67,83,86],"communicate":[37],"according":[38],"directed":[41],"network":[42],"topology.":[43],"Each":[44],"node":[45],"estimates":[46],"asynchronously":[50],"is":[52],"subject":[53],"local":[55],"(within-group)":[56],"regularization":[57,62],"global":[59],"(across":[60],"groups)":[61],"terms":[63],"targeting":[64],"noise":[65],"reduction":[66],"generalization":[68],"performance":[69],"improvement,":[70],"respectively.":[71],"provide":[73],"finite-time":[75],"characterization":[76],"of":[77,80,92],"the":[78,81,88],"convergence":[79],"estimators":[82],"task":[84],"relation":[85],"illustrate":[87],"scheme\u2019s":[89],"general":[90],"applicability":[91],"random":[93],"field":[94],"temperature":[95],"estimation.":[96]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}