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Learning Discrete Representations via Information Maximizing Self-Augmented Training.

W. Hu, T. Miyato, S. Tokui, E. Matsumoto, and M. Sugiyama. ICML, volume 70 of Proceedings of Machine Learning Research, page 1558-1567. PMLR, (2017)

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Takeru Onoda

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Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised LearningT. Miyato, S. Maeda, M. Koyama, and S. Ishii. (2017)cite arxiv:1704.03976Comment: To be appeared in IEEE Transactions on Pattern Analysis and Machine Intelligence.Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning.T. Miyato, S. ichi Maeda, M. Koyama, and S. Ishii. IEEE Trans. Pattern Anal. Mach. Intell., 41 (8): 1979-1993 (2019)Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration.R. Suzuki, M. Koyama, T. Miyato, and T. Yonetsuji. CoRR, (2018)GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers.T. Miyato, B. Jaeger, M. Welling, and A. Geiger. ICLR, OpenReview.net, (2024)Neural Fourier Transform: A General Approach to Equivariant Representation Learning.M. Koyama, K. Fukumizu, K. Hayashi, and T. Miyato. ICLR, OpenReview.net, (2024)Synthetic Gradient Methods with Virtual Forward-Backward Networks.T. Miyato, D. Okanohara, S. ichi Maeda, and M. Koyama. ICLR (Workshop), OpenReview.net, (2017)Adversarial Training Methods for Semi-Supervised Text Classification.T. Miyato, A. Dai, and I. Goodfellow. ICLR (Poster), OpenReview.net, (2017)Learning Discrete Representations via Information Maximizing Self-Augmented Training.W. Hu, T. Miyato, S. Tokui, E. Matsumoto, and M. Sugiyama. ICML, volume 70 of Proceedings of Machine Learning Research, page 1558-1567. PMLR, (2017)Robustness to Adversarial Perturbations in Learning from Incomplete Data.A. Najafi, S. ichi Maeda, M. Koyama, and T. Miyato. NeurIPS, page 5542-5552. (2019)Unsupervised Learning of Equivariant Structure from Sequences.T. Miyato, M. Koyama, and K. Fukumizu. NeurIPS, (2022)

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Learning Discrete Representations via Information Maximizing Self-Augmented Training.

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Takeru Onoda

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Disambiguation of "Miyato, Takeru"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learning Discrete Representations via Information Maximizing Self-Augmented Training.

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Takeru Onoda

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Learning Discrete Representations via Information Maximizing Self-Augmented Training.