Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

13 April 2017

Papers citing "Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning"

11 / 1,261 papers shown

Title
Smooth Neighbors on Teacher Graphs for Semi-supervised Learning Yucen Luo Jun Zhu Mengxi Li Yong Ren Bo Zhang 19 242 0 01 Nov 2017
Projection Based Weight Normalization for Deep Neural Networks Lei Huang Xianglong Liu B. Lang Bo-wen Li 28 18 0 06 Oct 2017
Machine learning methods for histopathological image analysis D. Komura S. Ishikawa 15 693 0 04 Sep 2017
Efficient Defenses Against Adversarial Attacks Valentina Zantedeschi Maria-Irina Nicolae Ambrish Rawat AAML 13 297 0 21 Jul 2017
Adversarial Dropout for Supervised and Semi-supervised Learning Sungrae Park Jun-Keon Park Su-Jin Shin Il-Chul Moon GAN 35 174 0 12 Jul 2017
Self-ensembling for visual domain adaptation Geoffrey French Michal Mackiewicz M. Fisher 19 44 0 16 Jun 2017
Good Semi-supervised Learning that Requires a Bad GAN Zihang Dai Zhilin Yang Fan Yang William W. Cohen Ruslan Salakhutdinov GAN 22 481 0 27 May 2017
Regularizing deep networks using efficient layerwise adversarial training S. Sankaranarayanan Arpit Jain Rama Chellappa Ser Nam Lim AAML 30 96 0 22 May 2017
GAR: An efficient and scalable Graph-based Activity Regularization for semi-supervised learning Ozsel Kilinc Ismail Uysal 20 28 0 19 May 2017
Adversarial Training Methods for Semi-Supervised Text Classification Takeru Miyato Andrew M. Dai Ian Goodfellow GAN 18 1,052 0 25 May 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015