{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T05:25:01Z","timestamp":1780464301864,"version":"3.54.1"},"reference-count":16,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91748112"],"award-info":[{"award-number":["91748112"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"AFOSR","doi-asserted-by":"crossref","award":["FA9550-10-1-0567"],"award-info":[{"award-number":["FA9550-10-1-0567"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"crossref"}]},{"name":"CRC Program"},{"name":"NSERC DG Program"},{"name":"ERA Program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Control Syst. Lett."],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1109\/lcsys.2019.2913770","type":"journal-article","created":{"date-parts":[[2019,5,10]],"date-time":"2019-05-10T19:53:51Z","timestamp":1557518031000},"page":"601-606","source":"Crossref","is-referenced-by-count":23,"title":["On the Powerball Method: Variants of Descent Methods for Accelerated Optimization"],"prefix":"10.1109","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7858-0437","authenticated-orcid":false,"given":"Ye","family":"Yuan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mu","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8762-2299","authenticated-orcid":false,"given":"Jun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3192-3185","authenticated-orcid":false,"given":"Claire","family":"Tomlin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/9780470400531.eorms0698"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CCDC.2017.7978071"},{"key":"ref12","first-page":"265","article-title":"On optimization methods for deep learning","author":"le","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn (ICML)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref14","first-page":"26","article-title":"Lecture 6.5–RMSprop: Divide the gradient by a running average of its recent magnitude","volume":"4","author":"tieleman","year":"2012","journal-title":"Neural Netw Mach Learning"},{"key":"ref15","first-page":"2121","article-title":"Adaptive subgradient methods for online learning and stochastic optimization","volume":"12","author":"duchi","year":"2011","journal-title":"J Mach Learn Res"},{"key":"ref16","first-page":"13","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"Proc Int Conf Learn Represent (ICLR)ICLR"},{"key":"ref4","first-page":"2845","article-title":"Accelerated mirror descent in continuous and discrete time","author":"krichene","year":"2015","journal-title":"Proc 29th Annu Conf Neural Inf Process Syst (NIPS)"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/BF01589116"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1137\/15M1009597"},{"key":"ref8","first-page":"1058","article-title":"1-bit stochastic gradient descent and application to data-parallel distributed training of speech DNNs","author":"seide","year":"2014","journal-title":"Proc INTERSPEECH"},{"key":"ref7","author":"sastry","year":"1999","journal-title":"Nonlinear Systems Analysis Stability and Control"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898718669"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.1997.609245"},{"key":"ref9","first-page":"1","article-title":"A differential equation for modeling Nesterov’s accelerated gradient method: Theory and insights","volume":"17","author":"su","year":"2016","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Control Systems Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7782633\/8675702\/08701500.pdf?arnumber=8701500","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T21:14:42Z","timestamp":1657746882000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8701500\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":16,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/lcsys.2019.2913770","relation":{},"ISSN":["2475-1456"],"issn-type":[{"value":"2475-1456","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7]]}}}