{"id":"https://openalex.org/W2962961166","doi":"https://doi.org/10.1109/lcomm.2019.2930513","title":"Coded Decentralized Learning With Gradient Descent for Big Data Analytics","display_name":"Coded Decentralized Learning With Gradient Descent for Big Data Analytics","publication_year":2019,"publication_date":"2019-07-23","ids":{"openalex":"https://openalex.org/W2962961166","doi":"https://doi.org/10.1109/lcomm.2019.2930513","mag":"2962961166"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2019.2930513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2019.2930513","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/LCOMM.2019.2930513","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018202801","display_name":"Jing Yue","orcid":"https://orcid.org/0000-0002-7423-7196"},"institutions":[{"id":"https://openalex.org/I2800664555","display_name":"RISE Research Institutes of Sweden","ror":"https://ror.org/03nnxqz81","country_code":"SE","type":"other","lineage":["https://openalex.org/I2800664555"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Jing Yue","raw_affiliation_strings":["Reliable Wireless Lab, RISE Research Institutes of Sweden, Lund, Sweden"],"affiliations":[{"raw_affiliation_string":"Reliable Wireless Lab, RISE Research Institutes of Sweden, Lund, Sweden","institution_ids":["https://openalex.org/I2800664555"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037292846","display_name":"Ming Xiao","orcid":"https://orcid.org/0000-0002-5407-0835"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ming Xiao","raw_affiliation_strings":["Division of ISE, School of EECS, KTH Royal Institute of Technology, Stockholm, Sweden"],"affiliations":[{"raw_affiliation_string":"Division of ISE, School of EECS, KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018202801"],"corresponding_institution_ids":["https://openalex.org/I2800664555"],"apc_list":null,"apc_paid":null,"fwci":1.1573,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84266209,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"24","issue":"2","first_page":"362","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9962000250816345,"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":0.9936000108718872,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.712971031665802},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5738759636878967},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5238321423530579},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.496072381734848},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.29521363973617554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29391586780548096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10717779397964478}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.712971031665802},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5738759636878967},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5238321423530579},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.496072381734848},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29521363973617554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29391586780548096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10717779397964478}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lcomm.2019.2930513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2019.2930513","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"},{"id":"pmh:oai:zenodo.org:4247327","is_oa":true,"landing_page_url":"https://doi.org/10.1109/LCOMM.2019.2930513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:4247327","is_oa":true,"landing_page_url":"https://doi.org/10.1109/LCOMM.2019.2930513","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338438","display_name":"HORIZON EUROPE Marie Sklodowska-Curie Actions","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2111319461","https://openalex.org/W2161342511","https://openalex.org/W2268702383","https://openalex.org/W2515135035","https://openalex.org/W2609731728","https://openalex.org/W2757498728","https://openalex.org/W2884907414","https://openalex.org/W2885072262","https://openalex.org/W2935717345","https://openalex.org/W2962850796","https://openalex.org/W2963041503","https://openalex.org/W2963290814","https://openalex.org/W2963706835","https://openalex.org/W3100515187","https://openalex.org/W3111898548","https://openalex.org/W4302423127","https://openalex.org/W6738835244","https://openalex.org/W6741764668","https://openalex.org/W6779799172"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W4233347783","https://openalex.org/W2910064364","https://openalex.org/W4255224757"],"abstract_inverted_index":{"Machine":[0],"learning":[1,21,32,41],"is":[2,80,89],"an":[3],"effective":[4],"technique":[5],"for":[6,38,70],"big":[7,16],"data":[8,17],"analytics.":[9],"We":[10],"focus":[11],"on":[12],"the":[13,30,67,75,84],"study":[14],"of":[15,77,86],"analytics":[18],"with":[19],"decentralized":[20,31],"in":[22],"large-scale":[23,71],"networks.":[24],"Fountain":[25],"codes":[26],"are":[27,54],"applied":[28],"to":[29,34],"process":[33],"reduce":[35],"communication":[36,60,78],"load":[37,61],"exchanging":[39],"intermediate":[40],"parameters":[42],"among":[43],"fog":[44,87],"nodes.":[45],"Two":[46],"scenarios,":[47],"i.e.,":[48],"disjoint":[49],"datasets":[50],"and":[51],"overlapping":[52],"datasets,":[53],"analyzed.":[55],"Comparison":[56],"results":[57],"show":[58],"that":[59],"can":[62],"be":[63],"reduced":[64],"significantly":[65],"by":[66],"Fountain-based":[68],"scheme":[69],"networks,":[72],"especially":[73],"when":[74],"quality":[76],"links":[79],"relatively":[81],"bad":[82],"and/or":[83],"number":[85],"nodes":[88],"large.":[90]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-07-30T00:00:00"}
