450 citations
- The University of TokyoJP19 papers
- Kyoto UniversityJP6 papers
- RIKEN Center for Advanced Intelligence ProjectJP5 papers
- National Institute of InformaticsJP4 papers
- RIKENJP3 papers
- Tohoku UniversityJP3 papers
- University of TsukubaJP3 papers
- Johns Hopkins UniversityUS2 papers
- Keio UniversityJP2 papers
- Kobe UniversityJP2 papers
- Massachusetts Institute of TechnologyUS2 papers
- Nara Institute of Science and TechnologyJP2 papers
Showing 2017 · stat.MLShow all
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stat.ML2017★ 213 cited
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama +1
We propose a new regularization method based on virtual adversarial loss: a new measure of local smoothness of the conditional label distribution given input. Virtual adversarial l…
stat.ML2017★ 291 cited
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu, Takeru Miyato, Seiya Tokui +2
Learning discrete representations of data is a central machine learning task because of the compactness of the representations and ease of interpretation. The task includes cluster…