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"

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Title
L_DMI: An Information-theoretic Noise-robust Loss Function Yilun Xu Peng Cao Yuqing Kong Yizhou Wang NoLa 19 57 0 08 Sep 2019
Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets Yang Li Jianhe Yuan Zhiqun Zhao Hao Sun Zhihai He 16 6 0 04 Sep 2019
Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning Zhanghan Ke Daoye Wang Qiong Yan Jimmy S. J. Ren Rynson W. H. Lau 19 213 0 03 Sep 2019
MetaMixUp: Learning Adaptive Interpolation Policy of MixUp with Meta-Learning Zhijun Mai Guosheng Hu Dexiong Chen Fumin Shen Heng Tao Shen 22 41 0 27 Aug 2019
Semi-Supervised Semantic Segmentation with High- and Low-level Consistency Sudhanshu Mittal Maxim Tatarchenko Thomas Brox SSL 22 372 0 15 Aug 2019
Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification Lei Qi Lei Wang Jing Huo Yinghuan Shi Yang Gao 27 45 0 15 Aug 2019
Neural Plasticity Networks Yong Li Shihao Ji 20 1 0 13 Aug 2019
Semi-Supervised Self-Growing Generative Adversarial Networks for Image Recognition Haoqian Wang Zhiwei Xu Jun Xu Wangpeng An Lei Zhang Qionghai Dai GAN 17 8 0 11 Aug 2019
Repetitive Reprediction Deep Decipher for Semi-Supervised Learning G. Wang Jianxin Wu 11 30 0 09 Aug 2019
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning Eric Arazo Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness 34 819 0 08 Aug 2019
Semi-supervised Thai Sentence Segmentation Using Local and Distant Word Representations Chanatip Saetia Ekapol Chuangsuwanich Tawunrat Chalothorn P. Vateekul 23 5 0 04 Aug 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 50 844 0 31 Jul 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 23 230 0 24 Jul 2019
Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence Garrett Wilson D. Cook 17 1 0 17 Jul 2019
Adversarial Lipschitz Regularization Dávid Terjék GAN 13 52 0 12 Jul 2019
Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks Ziliang Chen Jingyu Zhuang Xiaodan Liang Liang Lin OOD 33 83 0 08 Jul 2019
Fooling a Real Car with Adversarial Traffic Signs N. Morgulis Alexander Kreines Shachar Mendelowitz Yuval Weisglass AAML 6 91 0 30 Jun 2019
Learning Data Augmentation Strategies for Object Detection Barret Zoph E. D. Cubuk Golnaz Ghiasi Nayeon Lee Jonathon Shlens Quoc V. Le 39 523 0 26 Jun 2019
Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning Phi Vu Tran SSL 14 16 0 25 Jun 2019
Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy Angelica I. Aviles-Rivero Nicolas Papadakis Ruoteng Li P. Sellars Samar M. Alsaleh R. Tan Carola-Bibiane Schönlieb 27 3 0 20 Jun 2019
Learning Generalized Transformation Equivariant Representations via Autoencoding Transformations Guo-Jun Qi Liheng Zhang Tianlin Li OOD 20 39 0 19 Jun 2019
Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification Chia-Wen Kuo Chih-Yao Ma Jia-Bin Huang Z. Kira 6 2 0 12 Jun 2019
Selfie: Self-supervised Pretraining for Image Embedding Trieu H. Trinh Minh-Thang Luong Quoc V. Le SSL 11 111 0 07 Jun 2019
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy R. Dupre Jiri Fajtl Vasileios Argyriou Paolo Remagnino 19 2 0 06 Jun 2019
Semi-supervised semantic segmentation needs strong, varied perturbations Geoff French S. Laine Timo Aila Michal Mackiewicz G. Finlayson 33 29 0 05 Jun 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 17 13 0 04 Jun 2019
DualDis: Dual-Branch Disentangling with Adversarial Learning Thomas Robert Nicolas Thome Matthieu Cord CoGe DRL 33 4 0 03 Jun 2019
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training Jan Laermann Wojciech Samek Nils Strodthoff OOD 32 15 0 03 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He J. Hopcroft Liwei Wang 9 154 0 03 Jun 2019
Stochastic Generalized Adversarial Label Learning Chidubem Arachie Bert Huang NoLa 12 0 0 03 Jun 2019
Robust Learning Under Label Noise With Iterative Noise-Filtering D. Nguyen Thi-Phuong-Nhung Ngo Zhongyu Lou Michael Klar Laura Beggel Thomas Brox NoLa 14 16 0 01 Jun 2019
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice M. Das Devendra Singh Dhami Yang Yu Gautam Kunapuli Sriraam Natarajan 14 0 0 31 May 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 63 746 0 31 May 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 13 331 0 31 May 2019
Local Label Propagation for Large-Scale Semi-Supervised Learning Chengxu Zhuang Xuehao Ding Divyanshu Murli Daniel L. K. Yamins SSL 30 11 0 28 May 2019
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 16 77 0 27 May 2019
Unsupervised Domain Adaptation via Regularized Conditional Alignment Safa Cicek Stefano Soatto OOD 42 118 0 26 May 2019
Learning Smooth Representation for Unsupervised Domain Adaptation Guanyu Cai Lianghua He Mengchu Zhou H. Alhumade D. Hu 27 16 0 26 May 2019
Semi-supervised Learning with Contrastive Predicative Coding Jiaxing Wang Yin Zheng Xiaoshuang Chen Junzhou Huang Jian Cheng SSL 19 0 0 25 May 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 32 129 0 24 May 2019
Adversarially Robust Distillation Micah Goldblum Liam H. Fowl S. Feizi Tom Goldstein AAML 15 201 0 23 May 2019
Countering Noisy Labels By Learning From Auxiliary Clean Labels Tsung Wei Tsai Chongxuan Li Jun Zhu SSL 10 1 0 23 May 2019
Data-Efficient Image Recognition with Contrastive Predictive Coding Olivier J. Hénaff A. Srinivas J. Fauw Ali Razavi Carl Doersch S. M. Ali Eslami Aaron van den Oord SSL 58 1,417 0 22 May 2019
Semi-Supervised Learning with Scarce Annotations Sylvestre-Alvise Rebuffi Sébastien Ehrhardt Kai Han Andrea Vedaldi Andrew Zisserman SSL 24 49 0 21 May 2019
Semi-Supervised Learning by Augmented Distribution Alignment Qin Wang Wen Li Luc Van Gool 26 68 0 20 May 2019
What Do Adversarially Robust Models Look At? Takahiro Itazuri Yoshihiro Fukuhara Hirokatsu Kataoka Shigeo Morishima 19 5 0 19 May 2019
An Essay on Optimization Mystery of Deep Learning Eugene Golikov ODL 13 0 0 17 May 2019
Semi-supervised learning based on generative adversarial network: a comparison between good GAN and bad GAN approach Wenyuan Li Zichen Wang Jiayun Li J. Polson W. Speier C. Arnold GAN 14 22 0 16 May 2019
On Norm-Agnostic Robustness of Adversarial Training Bai Li Changyou Chen Wenlin Wang Lawrence Carin OOD SILM 8 7 0 15 May 2019
ROI Regularization for Semi-supervised and Supervised Learning H. Kaizuka Yasuhiro Nagasaki R. Sako 21 1 0 15 May 2019