{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T02:55:21Z","timestamp":1730343321397,"version":"3.28.0"},"reference-count":21,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,6]]},"DOI":"10.23919\/ecc.2018.8550538","type":"proceedings-article","created":{"date-parts":[[2018,12,8]],"date-time":"2018-12-08T00:50:06Z","timestamp":1544230206000},"page":"489-494","source":"Crossref","is-referenced-by-count":0,"title":["OR-SAGA: Over-relaxed stochastic average gradient mapping algorithms for finite sum minimization"],"prefix":"10.23919","author":[{"given":"Ion","family":"Necoara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrei","family":"Patrascu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Non-asymptotic analysis of stochastic approximation algorithms for machine learning","author":"moulines","year":"2011","journal-title":"Advances in neural information processing systems"},{"key":"ref11","article-title":"Introductory Lectures on Convex Optimization: A Basic Course","author":"nesterov","year":"2004","journal-title":"Kluwer"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2010.12.010"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3182\/20140824-6-ZA-1003.01700"},{"key":"ref14","article-title":"Nonasymptotic convergence of stochastic proximal point algorithms for constrained convex optimization","author":"patrascu","year":"2018","journal-title":"Journal of Machine Learning Research"},{"key":"ref15","article-title":"Accelerated Stochastic Gradient Descent for Minimizing Finite Sums","author":"nitanda","year":"2016","journal-title":"Proc Artif Intell Stat"},{"key":"ref16","article-title":"A General Analysis of the Convergence of ADMM","author":"nishihara","year":"2015","journal-title":"ICML"},{"key":"ref17","article-title":"A stochastic gradient method with an exponential convergence rate for strongly-convex optimization with finite training sets","author":"le","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref18","first-page":"567","article-title":"Stochastic dual coordinate ascent methods for regularized loss minimization","volume":"14","author":"shalev-schwartz","year":"2013","journal-title":"Journal of Machine Learning Research"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ECC.2016.7810279"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.879312"},{"key":"ref6","article-title":"A simple practical accelerated method for finite sums","author":"defazio","year":"2016","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2013.02.060"},{"key":"ref8","article-title":"Accelerating stochastic gradient descent using predictive variance reduction","author":"johnson","year":"2013","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref7","article-title":"SAGA: A fast incremental gradient method with support for non-strongly convex composite objectives","author":"defazio","year":"2014","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref2","article-title":"Incremental aggregated proximal and augmented lagrangian algorithms","author":"bertsekas","year":"2015","journal-title":"arXiv 1509 09257"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3055399.3055448"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-010-0434-y"},{"key":"ref20","first-page":"1290","article-title":"Towards stability and optimality in stochastic gradient descent","author":"toulis","year":"2016","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1137\/140961791"}],"event":{"name":"2018 17th European Control Conference (ECC)","start":{"date-parts":[[2018,6,12]]},"location":"Limassol","end":{"date-parts":[[2018,6,15]]}},"container-title":["2018 European Control Conference (ECC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8496738\/8550039\/08550538.pdf?arnumber=8550538","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,23]],"date-time":"2020-08-23T22:52:05Z","timestamp":1598223125000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8550538\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6]]},"references-count":21,"URL":"https:\/\/doi.org\/10.23919\/ecc.2018.8550538","relation":{},"subject":[],"published":{"date-parts":[[2018,6]]}}}