Jongchan/semi-supervised-learning-papers

semi-supervised-learning-papers

• List of deep semi-supervised learning
• Awesome Self-Supervised Learning can be a good reference, too.
• Any suggestions are welcomed via issues, PR, or email

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~2018

• Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks

  • Published at: ICML 2013 workshop
  • Author(s): Dong-Hyun Lee

• TEMPORAL ENSEMBLING FOR SEMI-SUPERVISED LEARNING

  • Published at: ICLR 2017
  • Author(s): Samuli Laine, and Timo Aila

• Regularization with stochastic transformations and perturbations for deep semi-supervised learning

  • Published at: NeurIPS 2016
  • Author(s): Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen

• Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results

  • Published at: NeurIPS 2017
  • Author(s): Antti Tarvainen, and Harri Valpola

2018

• Realistic Evaluation of Deep Semi-Supervised Learning Algorithms

  • Published at: NeurIPS 2018
  • Author(s): Avital Oliver, Augustus Odena, Colin A. Raffel, Ekin Dogus Cubuk, and Ian Goodfellow

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

  • Published at: TPAMI 2018 July
  • Author(s): Takeru Miyato, Shin-Ichi Maeda, Masanori Koyama, and Shin Ishii

2019

• Unsupervised Data Augmentation for Consistency Training

  • Published at: ArXiv pre-print 2019
  • Author(s): Qizhe Xie, Zihang Dai, Eduard Hovy, Minh-Thang Luong and Quoc V. Le

• S4L: Self-Supervised Semi-Supervised Learning

  • Published at: ArXiv pre-print 2019
  • Author(s): Xiaohua Zhai, Avital Oliver, Alexander Kolesnikov, and Lucas Beyer

• Local Label Propagation for Large-Scale Semi-Supervised Learning

  • Published at: ArXiv pre-print 2019
  • Author(s): Chengxu Zhuang, Xuehao Ding, Divyanshu Murli, and Daniel Yamins

• Billion-scale semi-supervised learning for image classification

  • Published at: ArXiv pre-print 2019
  • Author(s): I. Zeki Yalniz, Hervé Jégou, Kan Chen, Manohar Paluri, and Dhruv Mahajan

• Interpolation Consistency Training for Semi-Supervised Learning

  • Published at: IJCAI 2019
  • Author(s): Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, and David Lopez-Paz

• MixMatch: A Holistic Approach to Semi-Supervised Learning

  • Published at: ArXiv pre-print 2019
  • Author(s): David Berthelot, Nicholas Carlini, Ian Goodfellow, Nicolas Papernot, Avital Oliver, Colin Raffel

• Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets

  • Published at: arXiv pre-print 2019
  • Author(s): Yang Li, Jianhe Yuan, Zhiqun Zhao, Hao Sun, and Zhihai He
  • Experiment results:

2020

• Meta Pseudo Labels
  • Published at: arXiv pre-print 2020
  • Author(s): Hieu Pham, Qizhe Xie, Zihang Dai, and Quoc V. Le