| Preventing gradient explosions in gated recurrent units S Kanai, Y Fujiwara, S Iwamura Advances in neural information processing systems 30, 2017 | 117 | 2017 |
| Sigsoftmax: Reanalysis of the softmax bottleneck S Kanai, Y Fujiwara, Y Yamanaka, S Adachi Advances in Neural Information Processing Systems 31, 2018 | 77 | 2018 |
| Autoencoding binary classifiers for supervised anomaly detection Y Yamanaka, T Iwata, H Takahashi, M Yamada, S Kanai PRICAI 2019: Trends in Artificial Intelligence: 16th Pacific Rim …, 2019 | 38 | 2019 |
| Effective data augmentation with multi-domain learning gans S Yamaguchi, S Kanai, T Eda Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6566-6574, 2020 | 26 | 2020 |
| Image enhanced rotation prediction for self-supervised learning S Yamaguchi, S Kanai, T Shioda, S Takeda 2021 IEEE International Conference on Image Processing (ICIP), 489-493, 2021 | 9 | 2021 |
| Fast similarity computation for t-SNE Y Fujiwara, Y Ida, S Kanai, A Kumagai, N Ueda 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1691-1702, 2021 | 9 | 2021 |
| Fast deterministic CUR matrix decomposition with accuracy assurance Y Ida, S Kanai, Y Fujiwara, T Iwata, K Takeuchi, H Kashima International Conference on Machine Learning, 4594-4603, 2020 | 9 | 2020 |
| Multiple pretext-task for self-supervised learning via mixing multiple image transformations S Yamaguchi, S Kanai, T Shioda, S Takeda arXiv preprint arXiv:1912.11603, 2019 | 9 | 2019 |
| Smoothness analysis of adversarial training S Kanai, M Yamada, H Takahashi, Y Yamanaka, Y Ida arXiv preprint arXiv:2103.01400, 2021 | 8 | 2021 |
| Relationship between nonsmoothness in adversarial training, constraints of attacks, and flatness in the input space S Kanai, M Yamada, H Takahashi, Y Yamanaka, Y Ida IEEE Transactions on Neural Networks and Learning Systems, 2023 | 6 | 2023 |
| Adversarial training makes weight loss landscape sharper in logistic regression M Yamada, S Kanai, T Iwata, T Takahashi, Y Yamanaka, H Takahashi, ... arXiv preprint arXiv:2102.02950, 2021 | 5 | 2021 |
| Fast algorithm for anchor graph hashing Y Fujiwara, S Kanai, Y Ida, A Kumagai, N Ueda Proceedings of the VLDB Endowment 14 (6), 916-928, 2021 | 4 | 2021 |
| F-Drop&Match: GANs with a dead zone in the high-frequency domain S Yamaguchi, S Kanai Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 4 | 2021 |
| Fast random forest algorithm via incremental upper bound Y Fujiwara, Y Ida, S Kanai, A Kumagai, J Arai, N Ueda Proceedings of the 28th ACM International Conference on Information and …, 2019 | 4 | 2019 |
| One-vs-the-rest loss to focus on important samples in adversarial training S Kanai, S Yamaguchi, M Yamada, H Takahashi, K Ohno, Y Ida International Conference on Machine Learning, 15669-15695, 2023 | 3 | 2023 |
| Learning optimal priors for task-invariant representations in variational autoencoders H Takahashi, T Iwata, A Kumagai, S Kanai, M Yamada, Y Yamanaka, ... Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 3 | 2022 |
| Constraining logits by bounded function for adversarial robustness S Kanai, M Yamada, S Yamaguchi, H Takahashi, Y Ida 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 3 | 2021 |
| Accelerate inference of CNNs for video analysis while preserving exactness exploiting activation sparsity T Wakatsuki, S Kanai, Y Fujiwara Proceedings of Machine Learning and Systems 3, 860-872, 2021 | 3 | 2021 |
| Efficient Algorithm for the b-Matching Graph Y Fujiwara, A Kumagai, S Kanai, Y Ida, N Ueda Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 3 | 2020 |
| Efficient data point pruning for one-class SVM Y Fujiwara, S Kanai, J Arai, Y Ida, N Ueda Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3590-3597, 2019 | 3 | 2019 |
