| Learning from complementary labels T Ishida, G Niu, W Hu, M Sugiyama Advances in neural information processing systems (NeurIPS 2017), 2017 | 165 | 2017 |
| Do We Need Zero Training Loss After Achieving Zero Training Error? T Ishida, I Yamane, T Sakai, G Niu, M Sugiyama International Conference on Machine Learning (ICML 2020), 2020 | 133 | 2020 |
| Complementary-label learning for arbitrary losses and models T Ishida, G Niu, AK Menon, M Sugiyama International Conference on Machine Learning (ICML 2019), 2019 | 93 | 2019 |
| Binary classification from positive-confidence data T Ishida, G Niu, M Sugiyama Advances in neural information processing systems (NeurIPS 2018), 2018 | 70 | 2018 |
| Machine Learning from Weak Supervision: An Empirical Risk Minimization Approach M Sugiyama, H Bao, T Ishida, N Lu, T Sakai, G Niu MIT Press, 2022 | 21 | 2022 |
| LocalDrop: A hybrid regularization for deep neural networks Z Lu, C Xu, B Du, T Ishida, L Zhang, M Sugiyama IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (7), 3590-3601, 2021 | 19 | 2021 |
| Learning from Noisy Complementary Labels with Robust Loss Functions H ISHIGURO, T ISHIDA, M SUGIYAMA IEICE TRANSACTIONS on Information and Systems 105 (2), 364-376, 2022 | 7 | 2022 |
| Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification T Ishida, I Yamane, N Charoenphakdee, G Niu, M Sugiyama The Eleventh International Conference on Learning Representations (ICLR 2023), 2023 | 6 | 2023 |
| Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality I Yamane, Y Chevaleyre, T Ishida, F Yger International Conference on Artificial Intelligence and Statistics, 4768-4801, 2023 | 1 | 2023 |
| Learning with Complementary Labels Revisited: A Consistent Approach via Negative-Unlabeled Learning W Wang, T Ishida, YJ Zhang, G Niu, M Sugiyama arXiv preprint arXiv:2311.15502, 2023 | | 2023 |
| Flooding Regularization for Stable Training of Generative Adversarial Networks I Yahiro, T Ishida, N Yokoya arXiv preprint arXiv:2311.00318, 2023 | | 2023 |
