Semi-supervised-learning

Notes and codes of the topic "Semi-supervised learning"

[Lectures & Survey] Semi-supervised learning

• Graph-based Semi-supervised Learning, Zoubin Ghahramani, http://mlg.eng.cam.ac.uk/zoubin/talks/lect3ssl.pdf
• MLSS 2012: Z. Ghahramani - Lecture 3: Graph based semi-supervised learning (Part 1), https://www.youtube.com/watch?v=HZQOvm0fkLA&t=1363s
• Machine Learning CMU 10-605 Fall 2016, Lecture21 - SSL on Graphs, https://www.youtube.com/watch?v=4RrJUrmRrbc
• Bayesian Semi-Supervised Learning with Deep Generative Models, Presented by José-Miguel Hernández-Lobato, University of Cambridge at the Arm Research Summit 2017., https://www.youtube.com/watch?v=1ClZhMSHeBA
• Zhu, Xiaojin. "Semi-supervised learning literature survey." Computer Science, University of Wisconsin-Madison 2.3 (2006): 4.
• Chapelle, Olivier, Bernhard Scholkopf, and Alexander Zien. "Semi-supervised learning (chapelle, o. et al., eds.; 2006)[book reviews]." IEEE Transactions on Neural Networks 20.3 (2009): 542-542., http://www.acad.bg/ebook/ml/MITPress-%20SemiSupervised%20Learning.pdf

[Papers] Semi-supervised learning

Graph based

• Zhu, Xiaojin, and Zoubin Ghahramani. "Learning from labeled and unlabeled data with label propagation." (2002): 1.
• Zhu, Xiaojin, John Lafferty, and Zoubin Ghahramani. "Combining active learning and semi-supervised learning using gaussian fields and harmonic functions." ICML 2003 workshop on the continuum from labeled to unlabeled data in machine learning and data mining. Vol. 3. 2003.
• Kamnitsas, Konstantinos, et al. "Semi-Supervised Learning via Compact Latent Space Clustering." arXiv preprint arXiv:1806.02679 (2018)., https://www.youtube.com/watch?v=gdyZQ7vzVOw
• Anonymous authors, "Label propagation networks", https://openreview.net/forum?id=r1g7y2RqYX

Generative model based

• Kingma, Diederik P., et al. "Semi-supervised learning with deep generative models." Advances in Neural Information Processing Systems. 2014.
• Gordon, Jonathan, and José Miguel Hernández-Lobato. "Bayesian Semisupervised Learning with Deep Generative Models." arXiv preprint arXiv:1706.09751 (2017).
• Rasmus, Antti, et al. "Semi-supervised learning with ladder networks." Advances in Neural Information Processing Systems. 2015.
• Dai, Zihang, et al. "Good semi-supervised learning that requires a bad gan." Advances in Neural Information Processing Systems. 2017.

Others

• Laine, Samuli, and Timo Aila. "Temporal ensembling for semi-supervised learning." arXiv preprint arXiv:1610.02242 (2016).
• Vashishth, Shikhar, et al. "Confidence-based Graph Convolutional Networks for Semi-Supervised Learning." (2018).
• Tarvainen, Antti, and Harri Valpola. "Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results." Advances in neural information processing systems. 2017., https://github.com/CuriousAI/mean-teacher
• Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples (2014)." arXiv preprint arXiv:1412.6572. (Not for semi-supervised learning, but preliminary for VAT)
• Miyato, Takeru, et al. "Distributional smoothing with virtual adversarial training." arXiv preprint arXiv:1507.00677 (2015).
• Miyato, Takeru, et al. "Virtual adversarial training: a regularization method for supervised and semi-supervised learning." IEEE transactions on pattern analysis and machine intelligence (2018).
• Anonymous, Fast adversarial training for semi-supervised learning, https://openreview.net/forum?id=H1fsUiRcKQ

PU-learning

• Kiryo, Ryuichi, et al. "Positive-unlabeled learning with non-negative risk estimator." Advances in Neural Information Processing Systems. 2017.

Active learning

• Zhu, Xiaojin, John Lafferty, and Zoubin Ghahramani. "Combining active learning and semi-supervised learning using gaussian fields and harmonic functions." ICML 2003 workshop on the continuum from labeled to unlabeled data in machine learning and data mining. Vol. 3. 2003.