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Adversarial Dropout for Supervised and Semi-supervised Learning

12 July 2017

Papers citing "Adversarial Dropout for Supervised and Semi-supervised Learning"

27 / 27 papers shown

Title
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning Jingyang Li Jiachun Pan Vincent Y. F. Tan Kim-Chuan Toh Pan Zhou AAML MLT 135 0 0 15 Oct 2024
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning Takeru Miyato S. Maeda Masanori Koyama S. Ishii GAN 151 2,738 0 13 Apr 2017
Temporal Ensembling for Semi-Supervised Learning S. Laine Timo Aila UQCV 187 2,567 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 793 36,881 0 25 Aug 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 547 5,910 0 08 Jul 2016
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning Mehdi S. M. Sajjadi Mehran Javanmardi Tolga Tasdizen BDL 85 1,116 0 14 Jun 2016
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 486 9,067 0 10 Jun 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,196 0 16 Mar 2016
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF Xuezhe Ma Eduard H. Hovy 111 2,655 0 04 Mar 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans Diederik P. Kingma ODL 196 1,943 0 25 Feb 2016
Improved Dropout for Shallow and Deep Learning Zhe Li Boqing Gong Tianbao Yang BDL SyDa 87 77 0 06 Feb 2016
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks Jost Tobias Springenberg GAN 87 745 0 19 Nov 2015
Semi-Supervised Learning with Ladder Networks Antti Rasmus Harri Valpola Mikko Honkala Mathias Berglund T. Raiko SSL 102 1,372 0 09 Jul 2015
Distributional Smoothing with Virtual Adversarial Training Takeru Miyato S. Maeda Masanori Koyama Ken Nakae S. Ishii 91 458 0 02 Jul 2015
Highway Networks R. Srivastava Klaus Greff Jürgen Schmidhuber 183 1,773 0 03 May 2015
To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout Prateek Jain Vivek Kulkarni Abhradeep Thakurta Oliver Williams 95 30 0 06 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,312 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014
Learning with Pseudo-Ensembles Philip Bachman O. Alsharif Doina Precup 89 602 0 16 Dec 2014
Deeply-Supervised Nets Chen-Yu Lee Saining Xie Patrick W. Gallagher Zhengyou Zhang Zhuowen Tu 350 2,243 0 18 Sep 2014
Analyzing noise in autoencoders and deep networks Ben Poole Jascha Narain Sohl-Dickstein Surya Ganguli 92 108 0 06 Jun 2014
Dropout Training for Support Vector Machines Ning Chen Jun Zhu Jianfei Chen Bo Zhang 79 37 0 16 Apr 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 284 14,963 1 21 Dec 2013
Network In Network Min Lin Qiang Chen Shuicheng Yan 294 6,284 0 16 Dec 2013
Dropout Training as Adaptive Regularization Stefan Wager Sida I. Wang Percy Liang 129 600 0 04 Jul 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 463 7,667 0 03 Jul 2012