{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T15:45:02Z","timestamp":1781624702644,"version":"3.54.5"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,8,1]],"date-time":"2019-08-01T00:00:00Z","timestamp":1564617600000},"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":[],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1109\/ccta.2019.8920662","type":"proceedings-article","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T04:11:37Z","timestamp":1575605497000},"page":"136-141","source":"Crossref","is-referenced-by-count":3,"title":["Feedback Control for Online Training of Neural Networks"],"prefix":"10.1109","author":[{"given":"Zilong","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sophie","family":"Cerf","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bogdan","family":"Robu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Marchand","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/VCIP.2017.8305126"},{"key":"ref11","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009","journal-title":"Master's thesis Department of Computer Science University of Toronto"},{"key":"ref12","article-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms","author":"xiao","year":"2017","journal-title":"arXiv preprint arXiv 1708 07747"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s13244-018-0639-9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1968.sp008455"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/BF00344251"},{"key":"ref17","author":"chollet","year":"2015","journal-title":"Keras"},{"key":"ref4","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"0","journal-title":"Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics AISTATS 2010 Chia Laguna Resort Sardinia Italy May 13&#x2013;15 2010"},{"key":"ref3","article-title":"On quality control and machine learning in crowdsourcing","volume":"11","author":"lease","year":"2011","journal-title":"Human Computation"},{"key":"ref6","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume":"abs 1502 3167","author":"ioffe","year":"2015","journal-title":"CoRR"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-35289-8_26"},{"key":"ref8","article-title":"An overview of gradient descent optimization algorithms","author":"ruder","year":"2016","journal-title":"arXiv preprint arXiv 1609 09861"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2017.58"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2008.922970"},{"key":"ref1","article-title":"Lenet-5, convolutional neural networks","author":"lecun","year":"2015","journal-title":"url"},{"key":"ref9","article-title":"Wngrad: Learn the learning rate in gradient descent","author":"wu","year":"2018","journal-title":"arXiv preprint arXiv 1803 02865"}],"event":{"name":"2019 IEEE Conference on Control Technology and Applications (CCTA)","location":"Hong Kong, China","start":{"date-parts":[[2019,8,19]]},"end":{"date-parts":[[2019,8,21]]}},"container-title":["2019 IEEE Conference on Control Technology and Applications (CCTA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8911117\/8920394\/08920662.pdf?arnumber=8920662","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T10:49:11Z","timestamp":1658141351000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8920662\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/ccta.2019.8920662","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}