{"id":"https://openalex.org/W3012360060","doi":"https://doi.org/10.1109/cdc40024.2019.9029245","title":"Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach","display_name":"Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3012360060","doi":"https://doi.org/10.1109/cdc40024.2019.9029245","mag":"3012360060"},"language":"en","primary_location":{"id":"doi:10.1109/cdc40024.2019.9029245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"preprint","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/A5013868893","display_name":"Haibo Yang","orcid":"https://orcid.org/0000-0002-5715-0849"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haibo Yang","raw_affiliation_strings":["Department of Computer Science, Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100327403","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0002-0784-2038"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["Department of Statistics, Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056811906","display_name":"Minghong Fang","orcid":"https://orcid.org/0000-0002-1365-3911"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minghong Fang","raw_affiliation_strings":["Department of Computer Science, Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100409741","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0003-0383-0934"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jia Liu","raw_affiliation_strings":["Department of Computer Science, Iowa State University, Ames, IA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Iowa State University, Ames, IA, USA","institution_ids":["https://openalex.org/I173911158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013868893"],"corresponding_institution_ids":["https://openalex.org/I173911158"],"apc_list":null,"apc_paid":null,"fwci":2.3121,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.91434921,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5832","last_page":"5837"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/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/T11716","display_name":"Random Matrices and Applications","score":0.9898999929428101,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7511659264564514},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.7100343108177185},{"id":"https://openalex.org/keywords/mnist-database","display_name":"MNIST database","score":0.6642817258834839},{"id":"https://openalex.org/keywords/lipschitz-continuity","display_name":"Lipschitz continuity","score":0.6570245623588562},{"id":"https://openalex.org/keywords/byzantine-fault-tolerance","display_name":"Byzantine fault tolerance","score":0.6069342494010925},{"id":"https://openalex.org/keywords/coordinate-descent","display_name":"Coordinate descent","score":0.5409392714500427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47053062915802},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.451386958360672},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4096146523952484},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39621350169181824},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.34443140029907227},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.33833885192871094},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24602016806602478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17117822170257568},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.13361811637878418}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7511659264564514},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.7100343108177185},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.6642817258834839},{"id":"https://openalex.org/C22324862","wikidata":"https://www.wikidata.org/wiki/Q652707","display_name":"Lipschitz continuity","level":2,"score":0.6570245623588562},{"id":"https://openalex.org/C168021876","wikidata":"https://www.wikidata.org/wiki/Q1353446","display_name":"Byzantine fault tolerance","level":3,"score":0.6069342494010925},{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.5409392714500427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47053062915802},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.451386958360672},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4096146523952484},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39621350169181824},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.34443140029907227},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33833885192871094},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24602016806602478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17117822170257568},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.13361811637878418},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc40024.2019.9029245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc40024.2019.9029245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 58th Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2752689052","https://openalex.org/W2788308444","https://openalex.org/W2788816110","https://openalex.org/W2789903762","https://openalex.org/W2789911054","https://openalex.org/W2804165311","https://openalex.org/W2804948787","https://openalex.org/W2949384269","https://openalex.org/W2953384591","https://openalex.org/W2979956265","https://openalex.org/W3012360060","https://openalex.org/W4252654521","https://openalex.org/W6713134421","https://openalex.org/W6743821447","https://openalex.org/W6748268456","https://openalex.org/W6748626757","https://openalex.org/W6748786018","https://openalex.org/W6748805329","https://openalex.org/W6752181574","https://openalex.org/W6752246848","https://openalex.org/W6753124209","https://openalex.org/W6769137509"],"related_works":["https://openalex.org/W4315785049","https://openalex.org/W3015792155","https://openalex.org/W3118286710","https://openalex.org/W2937906318","https://openalex.org/W4225929918","https://openalex.org/W3095450733","https://openalex.org/W4286693783","https://openalex.org/W3175914740","https://openalex.org/W4294982320","https://openalex.org/W3034587794"],"abstract_inverted_index":{"In":[0,166],"this":[1,38],"work,":[2],"we":[3,40],"consider":[4],"the":[5,29,34,65,93,98,114,121,124,127,132],"resilience":[6],"of":[7,64,95,131],"distributed":[8,17],"algorithms":[9],"based":[10],"on":[11],"stochastic":[12],"gradient":[13],"descent":[14],"(SGD)":[15],"in":[16,79,120,152],"learning":[18],"with":[19,161],"potentially":[20],"Byzantine":[21,51,68],"attackers,":[22,69],"who":[23],"could":[24],"send":[25],"arbitrary":[26],"information":[27,91],"to":[28,32,49,62,75,142,179],"parameter":[30],"server":[31],"disrupt":[33],"training":[35,153],"process.":[36],"Toward":[37],"end,":[39],"propose":[41],"a":[42,76,173],"new":[43],"Lipschitz-inspired":[44],"coordinate-wise":[45],"median":[46],"approach":[47],"(LICM-SGD)":[48],"mitigate":[50],"attacks.":[52,137],"We":[53,138],"show":[54,143],"that":[55,123,130,144],"our":[56,83,109,145,167],"LICM-SGD":[57,146],"algorithm":[58,147],"can":[59],"resist":[60],"up":[61],"half":[63],"workers":[66],"being":[67],"while":[70],"still":[71],"converging":[72],"almost":[73],"surely":[74],"stationary":[77],"region":[78],"non-convex":[80],"settings.":[81],"Also,":[82],"LICM-":[84,110,169],"SGD":[85,111,134,170],"method":[86,112],"does":[87],"not":[88],"require":[89],"any":[90],"about":[92],"number":[94],"attackers":[96],"and":[97,157,163],"Lipschitz":[99],"constant,":[100],"which":[101],"makes":[102],"it":[103],"attractive":[104],"for":[105],"practical":[106],"implementations.":[107],"Moreover,":[108],"enjoys":[113],"optimal":[115],"O(md)":[116],"computational":[117,182],"time-":[118],"complexity":[119],"sense":[122],"time-complexity":[125],"is":[126],"same":[128],"as":[129],"standard":[133],"under":[135],"no":[136],"conduct":[139],"extensive":[140],"experiments":[141],"consistently":[148],"outperforms":[149],"existing":[150],"methods":[151],"multiclass":[154],"logistic":[155],"regression":[156],"convolutional":[158],"neural":[159],"networks":[160],"MNIST":[162],"CIFAR-10":[164],"datasets.":[165],"experiments,":[168],"also":[171],"achieves":[172],"much":[174],"faster":[175],"running":[176],"time":[177],"thanks":[178],"its":[180],"low":[181],"time-complexity.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}