{"id":"https://openalex.org/W4205878844","doi":"https://doi.org/10.1109/bigdata52589.2021.9671506","title":"Communication efficient distributed learning of neural networks in Big Data environments using Spark","display_name":"Communication efficient distributed learning of neural networks in Big Data environments using Spark","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W4205878844","doi":"https://doi.org/10.1109/bigdata52589.2021.9671506"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671506","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://publica.fraunhofer.de/documents/N-644621.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000707073","display_name":"Fouad Alkhoury","orcid":"https://orcid.org/0000-0001-9470-4890"},"institutions":[{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fouad Alkhoury","raw_affiliation_strings":["University of Bonn, Germany"],"affiliations":[{"raw_affiliation_string":"University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009621124","display_name":"Dennis Wegener","orcid":"https://orcid.org/0009-0009-8678-2093"},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dennis Wegener","raw_affiliation_strings":["Fraunhofer IAIS, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090677124","display_name":"Karl-Heinz Sylla","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karl-Heinz Sylla","raw_affiliation_strings":["Fraunhofer IAIS, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062749833","display_name":"Michael M\u00f6ck","orcid":"https://orcid.org/0009-0009-9864-8924"},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Mock","raw_affiliation_strings":["Fraunhofer IAIS, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Germany","institution_ids":["https://openalex.org/I4210144576"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000707073"],"corresponding_institution_ids":["https://openalex.org/I135140700"],"apc_list":null,"apc_paid":null,"fwci":0.2513,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52196672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","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/T11612","display_name":"Stochastic Gradient Optimization Techniques","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/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9990000128746033,"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/spark","display_name":"SPARK (programming language)","score":0.8374834656715393},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8276962637901306},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6393148303031921},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.635638415813446},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"Distributed learning","score":0.5995774269104004},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5489771962165833},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5188109278678894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5005536079406738},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4959016740322113},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4780176877975464},{"id":"https://openalex.org/keywords/distributed-database","display_name":"Distributed database","score":0.47737476229667664},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.45464688539505005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4234410524368286},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.25972992181777954}],"concepts":[{"id":"https://openalex.org/C2781215313","wikidata":"https://www.wikidata.org/wiki/Q3493345","display_name":"SPARK (programming language)","level":2,"score":0.8374834656715393},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8276962637901306},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6393148303031921},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.635638415813446},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.5995774269104004},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5489771962165833},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5188109278678894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5005536079406738},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4959016740322113},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4780176877975464},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.47737476229667664},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.45464688539505005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4234410524368286},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25972992181777954},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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":3,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671506","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671506","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","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":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-644621","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-644621.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"Fraunhofer IAIS","raw_type":"conferenceObject"},{"id":"pmh:oai:publica.fraunhofer.de:publica/413405","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/413405","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:fraunhofer.de:N-644621","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-644621.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"Fraunhofer IAIS","raw_type":"conferenceObject"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1508912423","https://openalex.org/W1525540222","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2150871235","https://openalex.org/W2163605009","https://openalex.org/W2173213060","https://openalex.org/W2186615578","https://openalex.org/W2189465200","https://openalex.org/W2336650964","https://openalex.org/W2395611524","https://openalex.org/W2472803348","https://openalex.org/W2515482415","https://openalex.org/W2788193959","https://openalex.org/W2798279844","https://openalex.org/W2962844195","https://openalex.org/W2963889845","https://openalex.org/W2984509121","https://openalex.org/W3016404858","https://openalex.org/W4292084264","https://openalex.org/W4295312788","https://openalex.org/W4301239768","https://openalex.org/W6677651945","https://openalex.org/W6684191040","https://openalex.org/W6686509673","https://openalex.org/W6687322159","https://openalex.org/W6687494587","https://openalex.org/W6703420464","https://openalex.org/W6711868289","https://openalex.org/W6748645090","https://openalex.org/W6750554607","https://openalex.org/W6752750811","https://openalex.org/W6766978945","https://openalex.org/W6776142756","https://openalex.org/W6891802897","https://openalex.org/W6982728064"],"related_works":["https://openalex.org/W3014300295","https://openalex.org/W3021430260","https://openalex.org/W3118882535","https://openalex.org/W2337926734","https://openalex.org/W3136076031","https://openalex.org/W2467826469","https://openalex.org/W2963898694","https://openalex.org/W2799614062","https://openalex.org/W4308353688","https://openalex.org/W3144574764"],"abstract_inverted_index":{"Distributed":[0],"(or":[1],"federated)":[2],"training":[3,14,45],"of":[4,36,46,132,138],"neural":[5,47,83],"networks":[6,48],"is":[7,40],"an":[8],"important":[9],"approach":[10,126],"to":[11,54,68,76,88,103],"reduce":[12],"the":[13,44,95,124,136],"time":[15],"significantly.":[16],"Previous":[17],"experiments":[18],"on":[19,111],"communication":[20,72,90],"efficient":[21,73,91],"distributed":[22,71,92,125],"learning":[23,74,93],"have":[24],"shown":[25],"that":[26,123],"model":[27],"averaging,":[28],"even":[29],"if":[30],"provably":[31],"correct":[32],"only":[33],"in":[34,49,135],"case":[35,137],"convex":[37],"loss":[38],"functions,":[39],"also":[41],"working":[42],"for":[43],"some":[50],"cases,":[51],"however":[52],"restricted":[53],"simple":[55],"examples":[56],"with":[57,129],"relatively":[58],"small":[59],"standard":[60],"data":[61,78,97,115],"sets.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66],"investigate":[67],"what":[69],"extent":[70],"scales":[75,127],"huge":[77],"sets":[79],"and":[80,100],"complex,":[81],"deep":[82],"networks.":[84,141],"We":[85,118],"show":[86],"how":[87],"integrate":[89],"into":[94],"big":[96],"environment":[98],"Spark":[99],"apply":[101],"it":[102],"a":[104,112],"complex":[105],"real-world":[106],"scenario,":[107],"namely":[108],"image":[109],"segmentation":[110],"large":[113],"automotive":[114],"set":[116],"(A2D2).":[117],"present":[119],"evidence":[120],"based":[121],"results":[122],"successfully":[128],"increasing":[130],"number":[131],"computing":[133],"nodes":[134],"fully":[139],"convolutional":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}