{"id":"https://openalex.org/W2954114036","doi":"https://doi.org/10.1109/tit.2020.3035868","title":"Data Encoding for Byzantine-Resilient Distributed Optimization","display_name":"Data Encoding for Byzantine-Resilient Distributed Optimization","publication_year":2020,"publication_date":"2020-11-04","ids":{"openalex":"https://openalex.org/W2954114036","doi":"https://doi.org/10.1109/tit.2020.3035868","mag":"2954114036"},"language":"en","primary_location":{"id":"doi:10.1109/tit.2020.3035868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2020.3035868","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Information Theory","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.02664","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023777978","display_name":"Deepesh Data","orcid":"https://orcid.org/0000-0003-3544-8414"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Deepesh Data","raw_affiliation_strings":["University of California at Los Angeles (UCLA), Los Angeles, CA, USA","Department of Electrical and Computer Engineering, University of California at Los Angeles (UCLA), Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California at Los Angeles (UCLA), Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California at Los Angeles (UCLA), Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035185924","display_name":"Linqi Song","orcid":"https://orcid.org/0000-0003-2756-4984"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]},{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK","US"],"is_corresponding":false,"raw_author_name":"Linqi Song","raw_affiliation_strings":["City University of Hong Kong, Hong Kong","University of California at Los Angeles (UCLA), Los Angeles, CA, USA","Department of Electrical and Computer Engineering, University of California at Los Angeles (UCLA), Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"University of California at Los Angeles (UCLA), Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of California at Los Angeles (UCLA), Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083980887","display_name":"Suhas Diggavi","orcid":"https://orcid.org/0000-0001-7313-9861"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Suhas N. Diggavi","raw_affiliation_strings":["City University of Hong Kong, Hong Kong","Computer Science Dept., City University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Computer Science Dept., City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5023777978"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.73429774,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74661932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"67","issue":"2","first_page":"1117","last_page":"1140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":1.0,"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":1.0,"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":0.9994999766349792,"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/T12056","display_name":"Markov Chains and Monte Carlo Methods","score":0.9973999857902527,"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/overhead","display_name":"Overhead (engineering)","score":0.7006947994232178},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6500816345214844},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6496515274047852},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6003736853599548},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.540452778339386},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4749743342399597},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46063339710235596},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4394252598285675},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3822749853134155},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24641594290733337},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.0901908278465271}],"concepts":[{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7006947994232178},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6500816345214844},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6496515274047852},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6003736853599548},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.540452778339386},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4749743342399597},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46063339710235596},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4394252598285675},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3822749853134155},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24641594290733337},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0901908278465271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tit.2020.3035868","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tit.2020.3035868","pdf_url":null,"source":{"id":"https://openalex.org/S4502562","display_name":"IEEE Transactions on Information Theory","issn_l":"0018-9448","issn":["0018-9448","1557-9654"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Information Theory","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1907.02664","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.02664","pdf_url":"https://arxiv.org/pdf/1907.02664","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:2954114036","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1907.02664","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1907.02664","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1907.02664","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.02664","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.02664","pdf_url":"https://arxiv.org/pdf/1907.02664","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":86,"referenced_works":["https://openalex.org/W19684845","https://openalex.org/W26556108","https://openalex.org/W114517082","https://openalex.org/W1506342804","https://openalex.org/W1603765807","https://openalex.org/W1967717294","https://openalex.org/W1969048569","https://openalex.org/W1982063824","https://openalex.org/W1994616650","https://openalex.org/W2000769684","https://openalex.org/W2032395696","https://openalex.org/W2056099894","https://openalex.org/W2095984592","https://openalex.org/W2112269233","https://openalex.org/W2120510885","https://openalex.org/W2129131372","https://openalex.org/W2129569662","https://openalex.org/W2141420453","https://openalex.org/W2153609494","https://openalex.org/W2166168182","https://openalex.org/W2166706236","https://openalex.org/W2168231600","https://openalex.org/W2173213060","https://openalex.org/W2265931279","https://openalex.org/W2268702383","https://openalex.org/W2296319761","https://openalex.org/W2397857137","https://openalex.org/W2614254310","https://openalex.org/W2729686365","https://openalex.org/W2741736887","https://openalex.org/W2752689052","https://openalex.org/W2807801669","https://openalex.org/W2913808958","https://openalex.org/W2935717345","https://openalex.org/W2940527161","https://openalex.org/W2946633206","https://openalex.org/W2949505878","https://openalex.org/W2962208489","https://openalex.org/W2962727278","https://openalex.org/W2962873681","https://openalex.org/W2963120442","https://openalex.org/W2963165390","https://openalex.org/W2963228337","https://openalex.org/W2963256807","https://openalex.org/W2963334472","https://openalex.org/W2963495269","https://openalex.org/W2963706835","https://openalex.org/W2964261056","https://openalex.org/W2964275427","https://openalex.org/W2964279249","https://openalex.org/W2970349186","https://openalex.org/W2976829912","https://openalex.org/W2977013187","https://openalex.org/W2992646835","https://openalex.org/W2997826898","https://openalex.org/W3006097074","https://openalex.org/W3025254786","https://openalex.org/W3034600652","https://openalex.org/W3035917281","https://openalex.org/W3111898548","https://openalex.org/W3137092842","https://openalex.org/W4250589301","https://openalex.org/W6676963778","https://openalex.org/W6677418025","https://openalex.org/W6684249991","https://openalex.org/W6684409620","https://openalex.org/W6684859321","https://openalex.org/W6730190955","https://openalex.org/W6738250615","https://openalex.org/W6741764668","https://openalex.org/W6742061381","https://openalex.org/W6743655711","https://openalex.org/W6743821447","https://openalex.org/W6748626757","https://openalex.org/W6748786018","https://openalex.org/W6748805329","https://openalex.org/W6749835716","https://openalex.org/W6752429284","https://openalex.org/W6752557422","https://openalex.org/W6754358263","https://openalex.org/W6762462524","https://openalex.org/W6763780468","https://openalex.org/W6766633873","https://openalex.org/W6777558252","https://openalex.org/W6779439156","https://openalex.org/W6779722313"],"related_works":["https://openalex.org/W3096199834","https://openalex.org/W2964261056","https://openalex.org/W2995022099","https://openalex.org/W2970349186","https://openalex.org/W2789911054","https://openalex.org/W2541884796","https://openalex.org/W3167719345","https://openalex.org/W2902116018","https://openalex.org/W2757498728","https://openalex.org/W3016695012","https://openalex.org/W3089170718","https://openalex.org/W2936505828","https://openalex.org/W3046631438","https://openalex.org/W3159302701","https://openalex.org/W3194742865","https://openalex.org/W1594030676","https://openalex.org/W1524363533","https://openalex.org/W3010127242","https://openalex.org/W2766727651","https://openalex.org/W2964333472"],"abstract_inverted_index":{"We":[0,133,147,163,178,259],"study":[1],"distributed":[2,16,217],"optimization":[3],"in":[4,85,100],"the":[5,46,86,101,109,161,183,187,215,226,233,249,266],"presence":[6],"of":[7,22,78,228,268],"Byzantine":[8],"adversaries,":[9],"where":[10,89,104],"both":[11],"data":[12,90,105,121,174,250],"and":[13,32,39,67,123,151,176,186,192,253],"computation":[14],"are":[15],"among":[17],"$m$":[18],"worker":[19,141],"machines,":[20],"$t$":[21],"which":[23,143,170,220],"may":[24,30],"be":[25],"corrupt.":[26],"The":[27],"compromised":[28],"nodes":[29],"collaboratively":[31],"arbitrarily":[33],"deviate":[34],"from":[35],"their":[36],"pre-specified":[37],"programs,":[38],"a":[40,75,117,165,180,204],"designated":[41],"(master)":[42],"node":[43],"iteratively":[44],"computes":[45],"model/parameter":[47],"vector":[48],"for":[49,198,254],"generalized":[50],"linear":[51],"models.":[52],"In":[53,112],"this":[54,113],"work,":[55],"we":[56,115],"primarily":[57],"focus":[58],"on":[59,120,160,208],"two":[60],"iterative":[61],"algorithms:":[62],"Proximal":[63],"Gradient":[64,71],"Descent":[65,69],"(PGD)":[66],"Coordinate":[68],"(CD).":[70],"descent":[72,257],"(GD)":[73],"is":[74,82,91,98,106,144,232],"special":[76],"case":[77],"these":[79,209],"algorithms.":[80],"PGD":[81],"typically":[83],"used":[84,99],"data-parallel":[87],"setting,":[88,103],"partitioned":[92,107],"across":[93,108],"different":[94],"samples,":[95],"whereas,":[96],"CD":[97,238],"model-parallelism":[102],"parameter":[110],"space.":[111],"paper,":[114],"propose":[116],"method":[118,153],"based":[119],"encoding":[122,168,175,244],"error":[124],"correction":[125],"over":[126,211],"real":[127],"numbers":[128],"to":[129,137,248,264],"combat":[130],"adversarial":[131,223,241],"attacks.":[132,242],"can":[134],"tolerate":[135],"up":[136],"$t\\leq":[138],"\\lfloor\\frac{m-1}{2}\\rfloor$":[139],"corrupt":[140],"nodes,":[142],"information-theoretically":[145],"optimal.":[146],"give":[148,261],"deterministic":[149],"guarantees,":[150],"our":[152,200,229,269],"does":[154],"not":[155],"assume":[156],"any":[157],"probability":[158],"distribution":[159],"data.":[162],"develop":[164],"{\\em":[166,205],"sparse}":[167],"scheme":[169,201,245],"enables":[171],"computationally":[172],"efficient":[173],"decoding.":[177],"demonstrate":[179],"trade-off":[181],"between":[182],"corruption":[184],"threshold":[185],"resource":[188],"requirements":[189],"(storage,":[190],"computational,":[191],"communication":[193],"complexity).":[194],"As":[195],"an":[196],"example,":[197],"$t\\leq\\frac{m}{3}$,":[199],"incurs":[202],"only":[203],"constant}":[206],"overhead":[207],"resources,":[210],"that":[212,236],"required":[213],"by":[214],"plain":[216],"PGD/CD":[218],"algorithms":[219],"provide":[221],"no":[222],"protection.":[224],"To":[225],"best":[227],"knowledge,":[230],"ours":[231],"first":[234],"paper":[235],"makes":[237],"secure":[239],"against":[240],"Our":[243],"extends":[246],"efficiently":[247],"streaming":[251],"model":[252],"stochastic":[255],"gradient":[256],"(SGD).":[258],"also":[260],"experimental":[262],"results":[263],"show":[265],"efficacy":[267],"proposed":[270],"schemes.":[271]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}