{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T13:28:22Z","timestamp":1762522102489,"version":"3.41.0"},"reference-count":12,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,10]]},"DOI":"10.1109\/smc.2017.8122736","type":"proceedings-article","created":{"date-parts":[[2017,11,30]],"date-time":"2017-11-30T22:22:47Z","timestamp":1512080567000},"page":"972-977","source":"Crossref","is-referenced-by-count":17,"title":["Controlled dropout: A different dropout for improving training speed on deep neural network"],"prefix":"10.1109","author":[{"given":"ByungSoo","family":"Ko","sequence":"first","affiliation":[]},{"given":"Han-Gyu","family":"Kim","sequence":"additional","affiliation":[]},{"given":"Ho-Jin","family":"Choi","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref4","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"Journal of Machine Learning Research"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3007818.3007832"},{"journal-title":"The MNIST Database of Handwritten Digits","year":"1998","author":"lecun","key":"ref10"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1021\/ci0342472"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref11"},{"key":"ref5","first-page":"358","article-title":"Controlled dropout: A different approach to using dropout on deep neural network","author":"ko","year":"2017","journal-title":"Big Data and Smart Computing (BigComp) 2017 IEEE International Conference on"},{"key":"ref12","first-page":"5","article-title":"Reading digits in natural images with unsupervised feature learning","volume":"2011","author":"netzer","year":"2011","journal-title":"NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref8","first-page":"1376","article-title":"Norm-based capacity control in neural networks","author":"neyshabur","year":"2015","journal-title":"COLT"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1109\/TNNLS.2012.2197412","article-title":"L1\/2 regularization: A thresholding representation theory and a fast solver","author":"xu","year":"2012","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"ref2","first-page":"2553","article-title":"Deep neural networks for object detection","author":"szegedy","year":"2013","journal-title":"Advances in neural information processing systems"},{"journal-title":"Complexity and Real Computation","year":"2012","author":"blum","key":"ref9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2015.69"}],"event":{"name":"2017 IEEE International Conference on Systems, Man and Cybernetics (SMC)","start":{"date-parts":[[2017,10,5]]},"location":"Banff, AB","end":{"date-parts":[[2017,10,8]]}},"container-title":["2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8114675\/8122565\/08122736.pdf?arnumber=8122736","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T22:18:31Z","timestamp":1751062711000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8122736\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":12,"URL":"https:\/\/doi.org\/10.1109\/smc.2017.8122736","relation":{},"subject":[],"published":{"date-parts":[[2017,10]]}}}