{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T04:49:07Z","timestamp":1782362947586,"version":"3.54.5"},"reference-count":15,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Network"],"published-print":{"date-parts":[[2023,9]]},"DOI":"10.1109\/mnet.132.2200530","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T18:45:25Z","timestamp":1675795525000},"page":"233-239","source":"Crossref","is-referenced-by-count":29,"title":["When Decentralized Optimization Meets Federated Learning"],"prefix":"10.1109","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0121-0953","authenticated-orcid":false,"given":"Hongchang","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0503-2012","authenticated-orcid":false,"given":"My T.","family":"Thai","sequence":"additional","affiliation":[{"name":"Department of Computer &#x0026; Information Sciences &#x0026; Engineering, University of Florida, Gainesville, FL, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3472-1717","authenticated-orcid":false,"given":"Jie","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1877","article-title":"Language models are few-shot learners","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Brown"},{"key":"ref2","first-page":"1","article-title":"Momentum-based variance reduction in non-convex SGD","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Cutkosky"},{"key":"ref3","article-title":"Sharpness-aware minimization for efficiently improving generalization","author":"Foret","year":"2020","journal-title":"arXiv:2010.01412"},{"key":"ref4","article-title":"Periodic stochastic gradient descent with momentum for decentralized training","author":"Gao","year":"2020","journal-title":"arXiv:2008.10435"},{"key":"ref5","article-title":"On large-batch training for deep learning: Generalization gap and sharp minima","author":"Keskar","year":"2016","journal-title":"arXiv:1609.04836"},{"key":"ref6","first-page":"1","article-title":"STEM: A stochastic two-sided momentum algorithm achieving near-optimal sample and communication complexities for federated learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Khanduri"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3126076"},{"key":"ref8","first-page":"1","article-title":"Can decentralized algorithms outperform centralized algorithms? A case study for decentralized parallel stochastic gradient descent","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Lian"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2922285"},{"key":"ref10","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist. (PMLR)","author":"McMahan"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-020-01487-0"},{"key":"ref12","article-title":"Black-box tuning for language-model-as-a-service","author":"Sun","year":"2022","journal-title":"arXiv:2201.03514"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2022.3153068"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-020-00082-4"},{"key":"ref15","article-title":"Applied federated learning: Improving Google keyboard query suggestions","author":"Yang","year":"2018","journal-title":"arXiv:1812.02903"}],"container-title":["IEEE Network"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/65\/10449707\/10038786.pdf?arnumber=10038786","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T18:41:37Z","timestamp":1709404897000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10038786\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,9]]},"references-count":15,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/mnet.132.2200530","relation":{},"ISSN":["0890-8044","1558-156X"],"issn-type":[{"value":"0890-8044","type":"print"},{"value":"1558-156X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,9]]}}}