{"id":"https://openalex.org/W2962741697","doi":"https://doi.org/10.3929/ethz-b-000282738","title":"CoCoA: A General Framework for Communication-Efficient Distributed Optimization","display_name":"CoCoA: A General Framework for Communication-Efficient Distributed Optimization","publication_year":2016,"publication_date":"2016-11-07","ids":{"openalex":"https://openalex.org/W2962741697","doi":"https://doi.org/10.3929/ethz-b-000282738","mag":"2962741697"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:1611.02189","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.02189","pdf_url":"https://arxiv.org/pdf/1611.02189","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1611.02189","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112800069","display_name":"Virginia Smith","orcid":"https://orcid.org/0000-0002-6404-2395","observed_orcids":["https://orcid.org/0000-0002-6404-2395"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, Virginia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052095147","display_name":"Simone Forte","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Forte, Simone","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101560932","display_name":"Chenxin Ma","orcid":"https://orcid.org/0000-0003-1761-6090","observed_orcids":["https://orcid.org/0000-0003-1761-6090"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chenxin, Ma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070679093","display_name":"Martin Tak\u00e1\u010d","orcid":"https://orcid.org/0000-0001-7455-2025","observed_orcids":["https://orcid.org/0000-0001-7455-2025"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tak\u00e1\u010d, Martin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049812527","display_name":"Michael I. Jordan","orcid":"https://orcid.org/0000-0001-8935-817X","observed_orcids":["https://orcid.org/0000-0001-8935-817X","https://orcid.org/0000-0002-2177-0405","https://orcid.org/0000-0002-5776-2626"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jordan, Michael I.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073756389","display_name":"Martin Jaggi","orcid":"https://orcid.org/0000-0003-1579-5558","observed_orcids":["https://orcid.org/0000-0003-1579-5558"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaggi, Martin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":221,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"230","first_page":"1","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9771000146865845,"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":0.9771000146865845,"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":0.014499999582767487,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.0010999999940395355,"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/distributed-optimization","display_name":"distributed optimization","score":0.8560000061988831},{"id":"https://openalex.org/keywords/communication-efficiency","display_name":"communication efficiency","score":0.7720000147819519},{"id":"https://openalex.org/keywords/l1-regularization","display_name":"L1 regularization","score":0.9229999780654907},{"id":"https://openalex.org/keywords/lasso","display_name":"LASSO","score":0.8579999804496765},{"id":"https://openalex.org/keywords/sparse-logistic-regression","display_name":"sparse logistic regression","score":0.9760000109672546},{"id":"https://openalex.org/keywords/elastic-net","display_name":"elastic net","score":0.8899999856948853},{"id":"https://openalex.org/keywords/convergence-guarantees","display_name":"convergence guarantees","score":0.7269999980926514},{"id":"https://openalex.org/keywords/distributed-learning","display_name":"distributed learning","score":0.6129999756813049}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6351178884506226},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.38931411504745483},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3855282962322235},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3580036163330078},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3408433496952057},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24137309193611145}],"mesh":[],"locations_count":9,"locations":[{"id":"pmh:oai:arXiv.org:1611.02189","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.02189","pdf_url":"https://arxiv.org/pdf/1611.02189","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"pmh:oai:infoscience.epfl.ch:262135","doi":null,"is_oa":true,"landing_page_url":"http://jmlr.org/papers/v18/16-512.html","pdf_url":"https://infoscience.epfl.ch/record/262135/files/16-512.pdf","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5124864","host_organization_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","host_organization_lineage":["https://openalex.org/I5124864"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"research article"},{"id":"pmh:oai:infoscience.tind.io:229237","doi":null,"is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/229237","pdf_url":"https://infoscience.epfl.ch/record/229237/files/1611.02189.pdf","source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5124864","host_organization_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","host_organization_lineage":["https://openalex.org/I5124864"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"},{"id":"pmh:oai:www.research-collection.ethz.ch:20.500.11850/282738","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11850/282738","pdf_url":"http://hdl.handle.net/20.500.11850/282738","source":{"id":"https://openalex.org/S4306402302","display_name":"Repository for Publications and Research Data (ETH Zurich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I35440088","host_organization_name":"ETH Zurich","host_organization_lineage":["https://openalex.org/I35440088"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research, 18","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:infoscience.epfl.ch:229237","doi":null,"is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/229237","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5124864","host_organization_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","host_organization_lineage":["https://openalex.org/I5124864"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:infoscience.epfl.ch:258517","doi":null,"is_oa":true,"landing_page_url":"http://infoscience.epfl.ch/record/258517","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I5124864","host_organization_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","host_organization_lineage":["https://openalex.org/I5124864"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://infoscience.epfl.ch/record/258517","raw_type":null},{"id":"doi:10.48550/arxiv.1611.02189","doi":"https://doi.org/10.48550/arxiv.1611.02189","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1611.02189","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.3929/ethz-b-000282738","doi":"https://doi.org/10.3929/ethz-b-000282738","is_oa":true,"landing_page_url":"https://doi.org/10.3929/ethz-b-000282738","pdf_url":null,"source":{"id":"https://openalex.org/S7407051236","display_name":"ETH Z\u00fcrich Research Collection","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:2962741697","doi":null,"is_oa":false,"landing_page_url":"https://jmlr.org/papers/volume18/16-512/16-512.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S118988714","display_name":"Journal of Machine Learning Research","issn_l":"1532-4435","issn":["1532-4435","1533-7928"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","ki-jl-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Journal of Machine Learning Research","raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1611.02189","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1611.02189","pdf_url":"https://arxiv.org/pdf/1611.02189","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1864889906","display_name":"Reliable Open-Source Large-Scale Machine Learning","funder_award_id":"175796","funder_id":"https://openalex.org/F4320320924","funder_display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung"},{"id":"https://openalex.org/G3041188381","display_name":"Collaborative Research:  TRIPODS Institute for Optimization and Learning","funder_award_id":"1740796","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5479629224","display_name":"GOALI: Machine Learning Approaches for Supply Chain Decision-Making","funder_award_id":"1663256","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G636044858","display_name":null,"funder_award_id":"N00014-15-1-2670","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"},{"id":"https://openalex.org/G8084227899","display_name":"AF: Small: New classes of optimization methods for nonconvex large scale machine learning models.","funder_award_id":"1618717","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8876996369","display_name":null,"funder_award_id":"N00014","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320924","display_name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","ror":"https://ror.org/00yjd3n13"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962741697.pdf","grobid_xml":"https://content.openalex.org/works/W2962741697.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1522126829","https://openalex.org/W1578527825","https://openalex.org/W1845160311","https://openalex.org/W2075660001","https://openalex.org/W2117669906","https://openalex.org/W2129421243","https://openalex.org/W2157711174","https://openalex.org/W2167732364","https://openalex.org/W2199097987","https://openalex.org/W2205688503","https://openalex.org/W2296319761"],"related_works":["https://openalex.org/W2287826714","https://openalex.org/W2522436252","https://openalex.org/W3126299544","https://openalex.org/W2952986481","https://openalex.org/W1968697355","https://openalex.org/W2143021454","https://openalex.org/W2966396637","https://openalex.org/W2963839817","https://openalex.org/W2889747079","https://openalex.org/W2790943930"],"abstract_inverted_index":{"The":[0,105],"scale":[1],"of":[2,8,39,87,122],"modern":[3],"datasets":[4],"necessitates":[5],"the":[6,49,85],"development":[7],"efficient":[9,29],"distributed":[10,22,126],"optimization":[11],"methods":[12],"for":[13,21,84],"machine":[14,42],"learning.":[15],"We":[16,47,80],"present":[17],"a":[18,36,77,94],"general-purpose":[19],"framework":[20,50,107],"computing":[23],"environments,":[24],"CoCoA,":[25],"that":[26],"has":[27,108],"an":[28,119],"communication":[30],"scheme":[31],"and":[32,44,64,68,101],"is":[33],"applicable":[34],"to":[35,51],"wide":[37],"variety":[38],"problems":[40,58],"in":[41,97],"learning":[43],"signal":[45],"processing.":[46],"extend":[48],"cover":[52],"general":[53],"non-strongly-convex":[54,99],"regularizers,":[55],"including":[56],"L1-regularized":[57],"like":[59],"lasso,":[60],"sparse":[61],"logistic":[62],"regression,":[63],"elastic":[65],"net":[66],"regularization,":[67],"show":[69],"how":[70],"earlier":[71],"work":[72],"can":[73],"be":[74],"derived":[75],"as":[76,115],"special":[78],"case.":[79],"provide":[81],"convergence":[82],"guarantees":[83],"class":[86],"convex":[88],"regularized":[89],"loss":[90,103],"minimization":[91],"objectives,":[92],"leveraging":[93],"novel":[95],"approach":[96],"handling":[98],"regularizers":[100],"non-smooth":[102],"functions.":[104],"resulting":[106],"markedly":[109],"improved":[110],"performance":[111],"over":[112],"state-of-the-art":[113],"methods,":[114],"we":[116],"illustrate":[117],"with":[118],"extensive":[120],"set":[121],"experiments":[123],"on":[124],"real":[125],"datasets.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":44},{"year":2020,"cited_by_count":41},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-07-30T00:00:00"}