{"id":"https://openalex.org/W4391022097","doi":"https://doi.org/10.1109/cdc49753.2023.10383603","title":"On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers","display_name":"On the Effects of Data Heterogeneity on the Convergence Rates of Distributed Linear System Solvers","publication_year":2023,"publication_date":"2023-12-13","ids":{"openalex":"https://openalex.org/W4391022097","doi":"https://doi.org/10.1109/cdc49753.2023.10383603"},"language":"en","primary_location":{"id":"doi:10.1109/cdc49753.2023.10383603","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cdc49753.2023.10383603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 62nd IEEE Conference on Decision and Control (CDC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023266166","display_name":"Boris Velasevic","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Boris Velasevic","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037649994","display_name":"Rohit Parasnis","orcid":"https://orcid.org/0000-0002-6922-450X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohit Parasnis","raw_affiliation_strings":["Purdue"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020399355","display_name":"Christopher G. Brinton","orcid":"https://orcid.org/0000-0003-2771-3521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christopher G. Brinton","raw_affiliation_strings":["Purdue"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005748450","display_name":"Navid Azizan","orcid":"https://orcid.org/0000-0002-4299-2963"},"institutions":[{"id":"https://openalex.org/I4210109586","display_name":"Moscow Institute of Thermal Technology","ror":"https://ror.org/021es5e59","country_code":"RU","type":"facility","lineage":["https://openalex.org/I4210109586"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Navid Azizan","raw_affiliation_strings":["MIT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MIT","institution_ids":["https://openalex.org/I4210109586"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"8394","last_page":"8399"},"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9983999729156494,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.989799976348877,"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/generality","display_name":"Generality","score":0.7615933418273926},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7341189384460449},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5898937582969666},{"id":"https://openalex.org/keywords/rate-of-convergence","display_name":"Rate of convergence","score":0.5832726955413818},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4879009425640106},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4680357277393341},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4455721974372864},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4282880425453186},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24603289365768433}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.7615933418273926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7341189384460449},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5898937582969666},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.5832726955413818},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4879009425640106},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4680357277393341},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4455721974372864},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4282880425453186},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24603289365768433},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc49753.2023.10383603","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cdc49753.2023.10383603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 62nd IEEE Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2473949271","display_name":null,"funder_award_id":"CNS-2146171","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W648150138","https://openalex.org/W1574975351","https://openalex.org/W1616857247","https://openalex.org/W1976013620","https://openalex.org/W1988720110","https://openalex.org/W2050949736","https://openalex.org/W2097460613","https://openalex.org/W2138243089","https://openalex.org/W2166706236","https://openalex.org/W2567931453","https://openalex.org/W2926987861","https://openalex.org/W2948566442","https://openalex.org/W2964102336","https://openalex.org/W3012125688","https://openalex.org/W3045259564","https://openalex.org/W3098532907","https://openalex.org/W3184519170","https://openalex.org/W3214217583","https://openalex.org/W4244375620","https://openalex.org/W4292363360","https://openalex.org/W4294732281","https://openalex.org/W4301621763","https://openalex.org/W4391022097","https://openalex.org/W6680402377","https://openalex.org/W6684249991","https://openalex.org/W6761030284","https://openalex.org/W6804490142","https://openalex.org/W6851839664"],"related_works":["https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818","https://openalex.org/W1522139108","https://openalex.org/W2353528968","https://openalex.org/W2032776242"],"abstract_inverted_index":{"We":[0],"consider":[1,16],"the":[2,17,25,32,45,62,66,72,93,101,110,141,145,150,176],"fundamental":[3],"problem":[4],"of":[5,10,34,37,44,65,71,86,124,144,152,168],"solving":[6,53],"a":[7,20,28,35,42,58,89,121,166,186],"large-scale":[8],"system":[9,26],"linear":[11],"equations.":[12,46],"In":[13,76],"particular,":[14],"we":[15,79,118,137],"setting":[18],"where":[19,183],"taskmaster":[21],"intends":[22],"to":[23],"solve":[24],"in":[27,165,180],"distributed/federated":[29],"fashion":[30],"with":[31,88],"help":[33],"set":[36],"machines,":[38],"who":[39],"each":[40,98],"have":[41],"subset":[43],"Although":[47],"there":[48,184],"exist":[49],"several":[50],"approaches":[51],"for":[52],"this":[54,77,116,135],"problem,":[55],"missing":[56],"is":[57,175,185],"rigorous":[59],"comparison":[60],"between":[61],"convergence":[63,142],"rates":[64,143],"projection-based":[67],"methods":[68],"and":[69,81,109,130,139,148,155],"those":[70],"optimization-":[73],"based":[74],"ones.":[75],"paper,":[78],"analyze":[80],"compare":[82,140],"these":[83,160],"two":[84],"classes":[85],"algorithms":[87,147],"particular":[90],"focus":[91],"on":[92,159],"most":[94,177],"efficient":[95,178],"method":[96,179],"from":[97],"class,":[99],"namely,":[100],"recently":[102],"proposed":[103],"Accelerated":[104],"Projection-Based":[105],"Consensus":[106],"(APC)":[107],"[1]":[108],"Distributed":[111],"Heavy-Ball":[112],"Method":[113],"(D-HBM).":[114],"To":[115],"end,":[117],"first":[119],"propose":[120],"geometric":[122],"notion":[123],"data":[125,157,188],"heterogeneity":[126,129,158],"called":[127],"angular":[128],"discuss":[131],"its":[132],"generality.":[133],"Using":[134],"notion,":[136],"bound":[138],"studied":[146],"capture":[149],"effects":[151],"both":[153],"cross-machine":[154],"local":[156],"quantities.":[161],"Our":[162,190],"analysis":[163],"results":[164],"number":[167],"novel":[169],"insights":[170],"besides":[171],"showing":[172],"that":[173],"APC":[174],"realistic":[181],"scenarios":[182],"large":[187],"heterogeneity.":[189],"numerical":[191],"analyses":[192],"validate":[193],"our":[194],"theoretical":[195],"results.":[196]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}