{"id":"https://openalex.org/W4312317960","doi":"https://doi.org/10.1109/tac.2022.3201141","title":"Improving the Transient Times for Distributed Stochastic Gradient Methods","display_name":"Improving the Transient Times for Distributed Stochastic Gradient Methods","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312317960","doi":"https://doi.org/10.1109/tac.2022.3201141"},"language":"en","primary_location":{"id":"doi:10.1109/tac.2022.3201141","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tac.2022.3201141","pdf_url":"https://ieeexplore.ieee.org/ielx7/9/4601496/09865230.pdf","source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/9/4601496/09865230.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038621489","display_name":"Kun Huang","orcid":"https://orcid.org/0000-0002-9326-6670"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Huang","raw_affiliation_strings":["School of Data Science, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-9326-6670","affiliations":[{"raw_affiliation_string":"School of Data Science, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032734653","display_name":"Shi Pu","orcid":"https://orcid.org/0000-0002-5813-527X"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Pu","raw_affiliation_strings":["School of Data Science, Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5813-527X","affiliations":[{"raw_affiliation_string":"School of Data Science, Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5083,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.84882286,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9970999956130981,"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":0.9970999956130981,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9955000281333923,"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"}},{"id":"https://openalex.org/T11347","display_name":"Neural Networks Stability and Synchronization","score":0.9890000224113464,"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/mathematics","display_name":"Mathematics","score":0.6554288268089294},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.5860394239425659},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.52601557970047},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.5213178992271423},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.49577149748802185},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4286850690841675},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4174148142337799},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.41577398777008057},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3869199752807617},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.351370632648468},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.35025209188461304},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.16688886284828186},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1129915714263916},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09114143252372742}],"concepts":[{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6554288268089294},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.5860394239425659},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.52601557970047},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.5213178992271423},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.49577149748802185},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4286850690841675},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4174148142337799},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.41577398777008057},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3869199752807617},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.351370632648468},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.35025209188461304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.16688886284828186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1129915714263916},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09114143252372742},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tac.2022.3201141","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tac.2022.3201141","pdf_url":"https://ieeexplore.ieee.org/ielx7/9/4601496/09865230.pdf","source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tac.2022.3201141","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tac.2022.3201141","pdf_url":"https://ieeexplore.ieee.org/ielx7/9/4601496/09865230.pdf","source":{"id":"https://openalex.org/S184954342","display_name":"IEEE Transactions on Automatic Control","issn_l":"0018-9286","issn":["0018-9286","1558-2523","2334-3303"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automatic Control","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3468160845","display_name":null,"funder_award_id":"J00120190011","funder_id":"https://openalex.org/F4320331102","funder_display_name":"Shenzhen Research Institute of Big Data"},{"id":"https://openalex.org/G458344280","display_name":null,"funder_award_id":"62003287","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6198259600","display_name":null,"funder_award_id":"Grant No. 62003287","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"},{"id":"https://openalex.org/F4320331102","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89"},{"id":"https://openalex.org/F4320333998","display_name":"Shenzhen Research Institute, City University of Hong Kong","ror":"https://ror.org/00xc0ma20"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312317960.pdf","grobid_xml":"https://content.openalex.org/works/W4312317960.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1571416372","https://openalex.org/W1966992934","https://openalex.org/W1982886636","https://openalex.org/W1992208280","https://openalex.org/W2010192956","https://openalex.org/W2027481851","https://openalex.org/W2029080014","https://openalex.org/W2044212084","https://openalex.org/W2056182476","https://openalex.org/W2057929279","https://openalex.org/W2081543628","https://openalex.org/W2082904296","https://openalex.org/W2112796928","https://openalex.org/W2114791779","https://openalex.org/W2129122308","https://openalex.org/W2136517470","https://openalex.org/W2154834860","https://openalex.org/W2266148951","https://openalex.org/W2552178850","https://openalex.org/W2586683640","https://openalex.org/W2609549560","https://openalex.org/W2615070957","https://openalex.org/W2659643337","https://openalex.org/W2737743075","https://openalex.org/W2763533254","https://openalex.org/W2783522756","https://openalex.org/W2805185133","https://openalex.org/W2899734758","https://openalex.org/W2962757173","https://openalex.org/W2962771678","https://openalex.org/W2963076621","https://openalex.org/W2963099310","https://openalex.org/W2963118811","https://openalex.org/W2963156126","https://openalex.org/W2963427711","https://openalex.org/W2963649943","https://openalex.org/W2964075583","https://openalex.org/W2964191394","https://openalex.org/W2964263318","https://openalex.org/W3006548771","https://openalex.org/W3011190964","https://openalex.org/W3011252985","https://openalex.org/W3022621540","https://openalex.org/W3042491641","https://openalex.org/W3047043330","https://openalex.org/W3047780503","https://openalex.org/W3100513551","https://openalex.org/W3214324039","https://openalex.org/W4281710948","https://openalex.org/W6738250615","https://openalex.org/W6748632073","https://openalex.org/W6756976665","https://openalex.org/W6758557334","https://openalex.org/W6777541487"],"related_works":["https://openalex.org/W3002546633","https://openalex.org/W2964170259","https://openalex.org/W2765682467","https://openalex.org/W4206119629","https://openalex.org/W4382937879","https://openalex.org/W4292651679","https://openalex.org/W2400034325","https://openalex.org/W2499557797","https://openalex.org/W4387635768","https://openalex.org/W4299515259"],"abstract_inverted_index":{"We":[0,66],"consider":[1],"the":[2,18,21,52,74,97,102,106,123,127,131,138,143,146,166],"distributed":[3,39],"optimization":[4],"problem":[5],"where":[6,117],"<inline-formula><tex-math":[7,22,113,118,147],"notation=\"LaTeX\">$n$</tex-math></inline-formula>":[8,23,148],"agents,":[9],"each":[10,155],"possessing":[11],"a":[12,27,38,62],"local":[13],"cost":[14,24,149,156],"function,":[15],"collaboratively":[16],"minimize":[17],"average":[19,144],"of":[20,126,133,145],"functions":[25,150],"over":[26],"connected":[28],"network.":[29],"Assuming":[30],"stochastic":[31,40,82],"gradient":[32,41,83],"information":[33],"is":[34,151,158],"available,":[35],"we":[36],"study":[37],"algorithm,":[42],"called":[43],"exact":[44],"diffusion":[45],"with":[46],"adaptive":[47],"stepsizes":[48],"(EDAS)":[49],"adapted":[50],"from":[51],"Exact":[53],"Diffusion":[54],"method":[55],"[1]":[56],"and":[57,60,90,154,164],"NIDS":[58],"[2]":[59],"perform":[61],"non-asymptotic":[63],"convergence":[64,78,108],"analysis.":[65],"not":[67],"only":[68],"show":[69],"that":[70],"EDAS":[71,136],"asymptotically":[72],"achieves":[73,137],"same":[75],"network":[76],"independent":[77],"rate":[79],"as":[80,112],"centralized":[81],"descent":[84],"(SGD)":[85],"for":[86,101,122],"minimizing":[87],"strongly":[88,152],"convex":[89,153],"smooth":[91],"objective":[92],"functions,":[93],"but":[94],"also":[95],"characterize":[96],"transient":[98,140],"time":[99,141],"needed":[100],"algorithm":[103],"to":[104],"approach":[105],"asymptotic":[107],"rate,":[109],"which":[110],"behaves":[111],"notation=\"LaTeX\">$K_{T}=\\mathcal":[114],"{O}(\\frac{n}{1-\\lambda":[115],"_{2}})$</tex-math></inline-formula>,":[116],"notation=\"LaTeX\">$1-\\lambda":[119],"_{2}$</tex-math></inline-formula>":[120],"stands":[121],"spectral":[124],"gap":[125],"mixing":[128],"matrix.":[129],"To":[130],"best":[132],"our":[134],"knowledge,":[135],"shortest":[139],"when":[142],"function":[157],"smooth.":[159],"Numerical":[160],"simulations":[161],"further":[162],"corroborate":[163],"strengthen":[165],"obtained":[167],"theoretical":[168],"results.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}