{"id":"https://openalex.org/W2900214122","doi":"https://doi.org/10.1109/tpds.2018.2879950","title":"Fast and Communication-Efficient Algorithm for Distributed Support Vector Machine Training","display_name":"Fast and Communication-Efficient Algorithm for Distributed Support Vector Machine Training","publication_year":2018,"publication_date":"2018-11-07","ids":{"openalex":"https://openalex.org/W2900214122","doi":"https://doi.org/10.1109/tpds.2018.2879950","mag":"2900214122"},"language":"en","primary_location":{"id":"doi:10.1109/tpds.2018.2879950","doi":"https://doi.org/10.1109/tpds.2018.2879950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpds.2018.2879950","pdf_url":null,"source":{"id":"https://openalex.org/S97130795","display_name":"IEEE Transactions on Parallel and Distributed Systems","issn_l":"1045-9219","issn":["1045-9219","1558-2183","2161-9883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-a","cwts-core","dongbi-a","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Parallel and Distributed Systems","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5065225892","display_name":"Jyotikrishna Dass","orcid":"https://orcid.org/0000-0002-7552-8753","observed_orcids":["https://orcid.org/0000-0002-7552-8753"]},"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":"Jyotikrishna Dass","raw_affiliation_strings":["Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-7552-8753","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111827824","display_name":"Vivek Sarin","orcid":null,"observed_orcids":[]},"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":"Vivek Sarin","raw_affiliation_strings":["Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103702897","display_name":"Rabi Mahapatra","orcid":"https://orcid.org/0000-0003-1702-8045","observed_orcids":["https://orcid.org/0000-0003-1702-8045"]},"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":"Rabi N. Mahapatra","raw_affiliation_strings":["Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":1.0878,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.8093058,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"30","issue":"5","first_page":"1065","last_page":"1076"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.8345000147819519,"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":0.8345000147819519,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.06620000302791595,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.019899999722838402,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/support-vector-machine-training","display_name":"support vector machine training","score":0.8960000276565552},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"distributed learning","score":0.8569999933242798},{"id":"https://openalex.org/keywords/communication-efficiency","display_name":"communication efficiency","score":0.9679999947547913},{"id":"https://openalex.org/keywords/kernel-matrix-approximation","display_name":"kernel matrix approximation","score":0.6110000014305115},{"id":"https://openalex.org/keywords/qr-decomposition","display_name":"QR decomposition","score":0.8610000014305115},{"id":"https://openalex.org/keywords/low-rank-approximation","display_name":"low-rank approximation","score":0.9649999737739563},{"id":"https://openalex.org/keywords/big-data-classification","display_name":"big data classification","score":0.621999979019165},{"id":"https://openalex.org/keywords/scalability","display_name":"scalability","score":0.7149999737739563},{"id":"https://openalex.org/keywords/linear-time-complexity","display_name":"linear time complexity","score":0.7369999885559082},{"id":"https://openalex.org/keywords/edge-computing","display_name":"edge computing","score":0.8579999804496765},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.7319999933242798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8814443349838257},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7016657590866089},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.692551851272583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.540444016456604},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5402562022209167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.539150059223175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5075525045394897},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4579635262489319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4237605035305023},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.41090285778045654},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3206368088722229},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.15542954206466675},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tpds.2018.2879950","doi":"https://doi.org/10.1109/tpds.2018.2879950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpds.2018.2879950","pdf_url":null,"source":{"id":"https://openalex.org/S97130795","display_name":"IEEE Transactions on Parallel and Distributed Systems","issn_l":"1045-9219","issn":["1045-9219","1558-2183","2161-9883"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-a","cwts-core","dongbi-a","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Parallel and Distributed Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334350","display_name":"High Performance Research Computing, Texas A and M University","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W31923072","https://openalex.org/W1506135481","https://openalex.org/W1551209770","https://openalex.org/W1574862351","https://openalex.org/W1575350781","https://openalex.org/W2092590148","https://openalex.org/W2099262739","https://openalex.org/W2101087512","https://openalex.org/W2109844857","https://openalex.org/W2117990954","https://openalex.org/W2137557016","https://openalex.org/W2139212933","https://openalex.org/W2139224857","https://openalex.org/W2150996188","https://openalex.org/W2153635508","https://openalex.org/W2157237396","https://openalex.org/W2164641162","https://openalex.org/W2165966284","https://openalex.org/W2171602483","https://openalex.org/W2412589610","https://openalex.org/W2735001126","https://openalex.org/W2974935665","https://openalex.org/W4292363360","https://openalex.org/W6676101543","https://openalex.org/W6681992919","https://openalex.org/W7034108470"],"related_works":["https://openalex.org/W2735001126","https://openalex.org/W4318148009","https://openalex.org/W3008771456","https://openalex.org/W4402601927","https://openalex.org/W2095885101","https://openalex.org/W7100675655","https://openalex.org/W2253790500","https://openalex.org/W1934946603","https://openalex.org/W3122443560","https://openalex.org/W2520178508"],"abstract_inverted_index":{"Support":[0],"Vector":[1],"Machines":[2],"(SVM)":[3],"are":[4,149],"widely":[5,154],"used":[6,155],"as":[7,182],"supervised":[8],"learning":[9],"models":[10],"to":[11,30,44,49,55,98,132,144,167],"solve":[12],"the":[13,51,85,92,106,123,158,168],"classification":[14],"problem":[15],"in":[16,115],"machine":[17],"learning.":[18],"Training":[19],"SVMs":[20],"for":[21,70,105,118,175],"large":[22],"datasets":[23],"is":[24,74,89,110],"an":[25],"extremely":[26],"challenging":[27],"task":[28],"due":[29],"excessive":[31],"storage":[32,103],"and":[33,54,76,102,140,186],"computational":[34],"requirements.":[35],"To":[36],"tackle":[37],"so-called":[38],"big":[39],"data":[40,128],"problems,":[41],"one":[42],"needs":[43],"design":[45],"scalable":[46,75],"distributed":[47,68,120],"algorithms":[48],"parallelize":[50],"model":[52],"training":[53,72,107,177],"develop":[56],"efficient":[57],"implementations":[58],"of":[59,84,95,122,170,189],"these":[60],"algorithms.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65],"propose":[66],"a":[67,81,119],"algorithm":[69,79,160],"SVM":[71,176],"that":[73],"communication-efficient.":[77],"The":[78],"uses":[80],"compact":[82],"representation":[83],"kernel":[86],"matrix,":[87],"which":[88],"based":[90],"on":[91,126,142,178],"QR":[93],"decomposition":[94],"low-rank":[96],"approximations,":[97],"reduce":[99],"both":[100],"computation":[101],"requirements":[104],"stage.":[108],"This":[109],"accompanied":[111],"by":[112],"considerable":[113],"reduction":[114],"communication":[116,138],"required":[117],"implementation":[121],"algorithm.":[124],"Experiments":[125],"benchmark":[127],"sets":[129],"with":[130,165],"up":[131,143],"five":[133],"million":[134],"samples":[135,171],"demonstrate":[136],"negligible":[137],"overhead":[139],"scalability":[141],"64":[145],"cores.":[146],"Execution":[147],"times":[148],"vast":[150],"improvements":[151],"over":[152],"other":[153],"packages.":[156],"Furthermore,":[157],"proposed":[159],"has":[161],"linear":[162],"time":[163],"complexity":[164],"respect":[166],"number":[169],"making":[172],"it":[173],"ideal":[174],"decentralized":[179],"environments":[180],"such":[181],"smart":[183],"embedded":[184],"systems":[185],"edge-based":[187],"internet":[188],"things,":[190],"IoT.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2018-11-16T00:00:00"}