Ryuichiro Hataya, and Hideki Nakayama, “DJMix: Unsupervised Task-agnostic Image Augmentation for Improving Robustness of Convolutional Neural Networks,” International Joint Conference on Neural Networks, 2022.
Taiga Kashima, Ryuichiro Hataya, and Hideki Nakayama, “Visualizing Association in Exemplar-based Classification.” International Conference on Acoustics, Speech, and Signal Processing, 2021.
Ryuichiro Hataya, and Hideki Nakayama, “LOL: Learning To Optimize Loss Switching Under Label Noise.” International Conference on Image Processing, 2019.
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Tatsuya Harada, and Ryuji Hamamoto, “Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval.” Machine Learning for Health Workshop at NeurIPS 2020. (Peer Reviewed, Extended Abstract)
Ryuichiro Hataya, Kumiko Matsui, and Tomoki Karasawa, “Learning to Identify Large Fossils using Deep Convolutional Neural Networks”, Geological Society of America Abstracts with Programs. Vol 52, No. 6, 2020.
Ryuichiro Hataya, and Hideki Nakayama, “Unifying semi-supervised and robust leaning by mixup.” Workshop on Learning from Limited Labeled Data at ICLR 2019, 2019. (Peer Reviewed, Spotlight)