{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:12:48Z","timestamp":1774631568197,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,9]]},"DOI":"10.1109\/mlsp.2016.7738878","type":"proceedings-article","created":{"date-parts":[[2016,11,10]],"date-time":"2016-11-10T21:40:41Z","timestamp":1478814041000},"page":"1-6","source":"Crossref","is-referenced-by-count":21,"title":["Stochastic gradient descent with finite samples sizes"],"prefix":"10.1109","author":[{"given":"Kun","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bicheng","family":"Ying","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Vlaski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali H.","family":"Sayed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/9780470374122"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1561\/2200000051"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1023\/A:1018366000512"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-6594-6_11"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"ref15","first-page":"1139","article-title":"On the importance of initialization and momentum in deep learning","author":"sutskever","year":"2013","journal-title":"Proc International Conference on Machine Learning (ICML)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2014.2306253"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/78.506609"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/S0005-1098(96)00136-7"},{"key":"ref19","first-page":"1017","article-title":"Stochastic gradient descent, weighted sampling, and the randomized kaczmarz algorithm","author":"needell","year":"2014","journal-title":"Proc Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref3","author":"polyak","year":"1987","journal-title":"Introduction to Optimization"},{"key":"ref6","first-page":"451","article-title":"Non-asymptotic analysis of stochastic approximation algorithms for machine learning","author":"moulines","year":"2011","journal-title":"Proc Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref5","first-page":"161","article-title":"The tradeoffs of large scale learning","author":"bousquet","year":"2008","journal-title":"Proc Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1137\/070704277"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015332"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1137\/0330046"},{"key":"ref1","author":"bertsekas","year":"1989","journal-title":"Parallel and Distributed Computation Numerical Methods"},{"key":"ref9","author":"haykin","year":"2008","journal-title":"Adaptive Filter Theory"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-010-0420-4"},{"key":"ref22","first-page":"1355","article-title":"Stochastic optimization with importance sampling for regularized loss minimization","author":"zhao","year":"2015","journal-title":"Proc International Conference on Machine Learning (ICML)"},{"key":"ref21","first-page":"1647","article-title":"Better mini-batch algorithms via accelerated gradient methods","author":"cotter","year":"2011","journal-title":"Proc Advances in Neural Information Processing Systems (NIPS)"}],"event":{"name":"2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)","location":"Vietri sul Mare, Salerno, Italy","start":{"date-parts":[[2016,9,13]]},"end":{"date-parts":[[2016,9,16]]}},"container-title":["2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7605057\/7738802\/07738878.pdf?arnumber=7738878","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2016,12,7]],"date-time":"2016-12-07T17:27:46Z","timestamp":1481131666000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7738878\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/mlsp.2016.7738878","relation":{},"subject":[],"published":{"date-parts":[[2016,9]]}}}