{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:56:09Z","timestamp":1760709369250,"version":"3.28.0"},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1109\/cybconf.2017.7985811","type":"proceedings-article","created":{"date-parts":[[2017,7,20]],"date-time":"2017-07-20T20:38:12Z","timestamp":1500583092000},"page":"1-5","source":"Crossref","is-referenced-by-count":12,"title":["SoftTarget Regularization: An Effective Technique to Reduce Over-Fitting in Neural Networks"],"prefix":"10.1109","author":[{"given":"Armen","family":"Aghajanyan","sequence":"first","affiliation":[]}],"member":"263","reference":[{"article-title":"Keras Deep Learning Library","year":"2015","author":"chollet","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/MCSE.2007.55"},{"article-title":"The MNIST Database","year":"1998","author":"lecun","key":"ref12"},{"key":"ref13","first-page":"1","article-title":"ADADELTA: An Adaptive Learning Rate Method","author":"zeiler","year":"2012","journal-title":"ArXiv"},{"key":"ref14","article-title":"Learning Multiple Layers of Features from Tiny Images","author":"krizhevsky","year":"2009","journal-title":"University of Toronto Toronto ON Tech Rep"},{"key":"ref15","first-page":"1","article-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","author":"loffe","year":"2015","journal-title":"ArXiv"},{"key":"ref16","first-page":"1097","article-title":"lmageNet Classification with Deep Convolutional Neural Networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref17","first-page":"92","author":"scherer","year":"2010","journal-title":"Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition"},{"key":"ref18","first-page":"1","article-title":"Reading Digits in Natural Images with Unsupervised Feature Learning","author":"netzer","year":"2011","journal-title":"NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref19","first-page":"1","article-title":"Deep Residual Learning for Image Recognition","author":"he","year":"2015","journal-title":"ArXiv"},{"key":"ref4","first-page":"1","article-title":"Distilling the Knowledge in a Neural Network","author":"hinton","year":"2015","journal-title":"ArXiv"},{"key":"ref3","first-page":"950","article-title":"A Simple Weight Decay Can Improve Generalization","volume":"4","author":"krogh","year":"1992","journal-title":"Advances in neural information processing systems"},{"key":"ref6","first-page":"1","article-title":"Training Deep Neural Networks on Noisy Labels with Bootstrapping","author":"reed","year":"2014","journal-title":"ArXiv"},{"key":"ref5","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"bergstra","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref8","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","author":"lee","year":"2013","journal-title":"Proceedings of ICML 2013 Workshop on Challenges in Representation Learning"},{"key":"ref7","first-page":"529","article-title":"Semi-supervised Learning by Entropy Minimization","volume":"17","author":"grandvalet","year":"2005","journal-title":"Network"},{"key":"ref2","first-page":"109","article-title":"Regularization of Neural Networks using DropConnect","author":"wan","year":"2013","journal-title":"Proceedings of the 30th International Conference on Machine Learning"},{"key":"ref1","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":"ref9","first-page":"19","article-title":"Theano: A Python framework for fast computation of mathematical expressions","year":"2016","journal-title":"T development team"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/0010-0277(81)90013-5"},{"key":"ref22","first-page":"27","article-title":"Principles of Categorization","author":"rosch","year":"1978","journal-title":"Cognition and Categorization"},{"key":"ref21","first-page":"482","article-title":"Categorization, prototype theory and neural dynamics","volume":"96","author":"duch","year":"1996","journal-title":"Proceedings of the 4th International Conference on Soft Computing"}],"event":{"name":"2017 3rd IEEE International Conference on Cybernetics (CYBCONF)","start":{"date-parts":[[2017,6,21]]},"location":"Exeter, United Kingdom","end":{"date-parts":[[2017,6,23]]}},"container-title":["2017 3rd IEEE International Conference on Cybernetics (CYBCONF)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7984317\/7985735\/07985811.pdf?arnumber=7985811","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,8,16]],"date-time":"2017-08-16T15:57:57Z","timestamp":1502899077000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7985811\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,6]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/cybconf.2017.7985811","relation":{},"subject":[],"published":{"date-parts":[[2017,6]]}}}