Jun-Keon Park

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All published works

Action	Title	Year	Authors
+ PDF Chat	Adversarial Dropout for Supervised and Semi-Supervised Learning	2018	Sungrae Park Jun-Keon Park Su-Jin Shin Il‐Chul Moon
+	Adversarial Dropout for Supervised and Semi-supervised Learning	2017	Sungrae Park Jun-Keon Park Su-Jin Shin Il‐Chul Moon
+	Adversarial Dropout for Supervised and Semi-supervised Learning	2017	Sungrae Park Jun-Keon Park Su‐Jin Shin Il‐Chul Moon

Common Coauthors

Coauthor	Papers Together
Il‐Chul Moon	3
Su-Jin Shin	2
Sungrae Park	2
Sungrae Park	1
Su‐Jin Shin	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Analyzing noise in autoencoders and deep networks	2014	Ben Poole Jascha Sohl‐Dickstein Surya Ganguli	2
+	To Drop or Not to Drop: Robustness, Consistency and Differential Privacy Properties of Dropout	2015	Prateek Jain Vivek Kulkarni Abhradeep Thakurta Oliver Williams	2
+	Improving neural networks by preventing co-adaptation of feature detectors	2012	Geoffrey E. Hinton Nitish Srivastava Alex Krizhevsky Ilya Sutskever Ruslan Salakhutdinov	2
+ PDF Chat	Identity Mappings in Deep Residual Networks	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	2
+	Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning	2016	Mehdi S. M. Sajjadi Mehran Javanmardi Tolga Taşdizen	2
+	Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning	2017	Takeru Miyato Shin‐ichi Maeda Masanori Koyama Shin Ishii	2
+	Temporal Ensembling for Semi-Supervised Learning	2016	Samuli Laine Timo Aila	2
+	Dropout Training as Adaptive Regularization	2013	Stefan Wager Sida Wang Percy Liang	2
+	Striving for Simplicity: The All Convolutional Net	2014	Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller	1
+	Learning with Pseudo-Ensembles	2014	Phil Bachman Ouais Alsharif Doina Precup	1
+	Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks	2015	Jost Tobias Springenberg	1
+	Improved Dropout for Shallow and Deep Learning	2016	Zhe Li Boqing Gong Tianbao Yang	1
+	Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks	2016	Tim Salimans Diederik P. Kingma	1
+	Distributional Smoothing with Virtual Adversarial Training	2016	Takeru Miyato Shin‐ichi Maeda Masanori Koyama Ken Nakae Shin Ishii	1
+	Improved Dropout for Shallow and Deep Learning	2016	Zhe Li Boqing Gong Tianbao Yang	1
+	Improved Techniques for Training GANs	2016	Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen	1
+	Adversarial examples in the physical world	2016	Alexey Kurakin Ian Goodfellow Samy Bengio	1
+	Densely Connected Convolutional Networks	2016	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	1
+	Nonlinear Integer Programming	2009	Raymond Hemmecke Matthias Köppe Jon Lee Robert Weismantel	1
+ PDF Chat	Dropout Training for Support Vector Machines	2014	Ning Chen Jun Zhu Jianfei Chen Bo Zhang	1
+	Adversarial examples in the physical world	2016	Alexey Kurakin Ian Goodfellow Samy Bengio	1
+	Distributional Smoothing with Virtual Adversarial Training	2015	Takeru Miyato Shin‐ichi Maeda Masanori Koyama Ken Nakae Shin Ishii	1
+ PDF Chat	End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF	2016	Xuezhe Ma Eduard Hovy	1
+	Network In Network	2013	Min Lin Qiang Chen Shuicheng Yan	1
+ PDF Chat	Densely Connected Convolutional Networks	2017	Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger	1
+	Dropout Training for Support Vector Machines	2014	Ning Chen Jun Zhu Jianfei Chen Bo Zhang	1
+	Explaining and Harnessing Adversarial Examples	2014	Ian Goodfellow Jonathon Shlens Christian Szegedy	1
+	Non-linear integer programming	1975	Leon N. Cooper Mary W. Cooper	1
+	Training with Noise is Equivalent to Tikhonov Regularization	1995	Chris Bishop	1