| Rethinking importance weighting for deep learning under distribution shift T Fang, N Lu, G Niu, M Sugiyama NeurIPS 2020, 2020 | 129 | 2020 |
| On the minimal supervision for training any binary classifier from only unlabeled data N Lu, G Niu, AK Menon, M Sugiyama ICLR 2019, 2018 | 93 | 2018 |
| Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach N Lu, T Zhang, G Niu, M Sugiyama AISTATS 2020, 2019 | 59 | 2019 |
| Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients N Lu, Z Wang, X Li, G Niu, Q Dou, M Sugiyama ICLR 2022, 2022 | 45 | 2022 |
| Machine learning from weak supervision: An empirical risk minimization approach M Sugiyama, H Bao, T Ishida, N Lu, T Sakai MIT Press, 2022 | 26 | 2022 |
| A one-step approach to covariate shift adaptation T Zhang, I Yamane, N Lu, M Sugiyama Asian Conference on Machine Learning, 65-80, 2020 | 23 | 2020 |
| Pointwise Binary Classification with Pairwise Confidence Comparisons L Feng, S Shu, N Lu, B Han, M Xu, G Niu, B An, M Sugiyama ICML 2021, 2020 | 22 | 2020 |
| Binary classification from multiple unlabeled datasets via surrogate set classification N Lu, S Lei, G Niu, I Sato, M Sugiyama ICML 2021, 2021 | 14 | 2021 |
| Rethinking Importance Weighting for Transfer Learning N Lu, T Zhang, T Fang, T Teshima, M Sugiyama Federated and Transfer Learning 27, 185–231, 2022 | 9 | 2022 |
| Multi-class classification from multiple unlabeled datasets with partial risk regularization Y Tang, N Lu, T Zhang, M Sugiyama Asian Conference on Machine Learning, 990-1005, 2023 | 4* | 2023 |
| A general framework for learning under corruption: Label noise, attribute noise, and beyond L Iacovissi, N Lu, RC Williamson arXiv preprint arXiv:2307.08643, 2023 | 3 | 2023 |
| Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems T Fang, N Lu, G Niu, M Sugiyama NeurIPS 2023, 2023 | 3 | 2023 |
| A One-Step Approach to Covariate Shift Adaptation T Zhang, I Yamane, N Lu, M Sugiyama SN Computer Science 2 (4), 1-12, 2021 | | 2021 |
