| A fully adaptive algorithm for pure exploration in linear bandits L Xu, J Honda, M Sugiyama International Conference on Artificial Intelligence and Statistics, 843-851, 2018 | 63 | 2018 |
| Polynomial-time algorithms for multiple-arm identification with full-bandit feedback Y Kuroki, L Xu, A Miyauchi, J Honda, M Sugiyama Neural Computation 32 (9), 1733-1773, 2020 | 14 | 2020 |
| Alternate estimation of a classifier and the class-prior from positive and unlabeled data M Kato, L Xu, G Niu, M Sugiyama arXiv preprint arXiv:1809.05710, 2018 | 10 | 2018 |
| Similarity-based classification: Connecting similarity learning to binary classification H Bao, T Shimada, L Xu, I Sato, M Sugiyama arXiv preprint arXiv:2006.06207, 2020 | 8 | 2020 |
| Uncoupled regression from pairwise comparison data L Xu, J Honda, G Niu, M Sugiyama Advances in Neural Information Processing Systems 32, 2019 | 6 | 2019 |
| Dueling bandits with qualitative feedback L Xu, J Honda, M Sugiyama Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5549-5556, 2019 | 4 | 2019 |
| Polynomial-time algorithms for combinatorial pure exploration with full-bandit feedback Y Kuroki, L Xu, A Miyauchi, J Honda, M Sugiyama | 4 | 2019 |
| Pairwise Supervision Can Provably Elicit a Decision Boundary H Bao, T Shimada, L Xu, I Sato, M Sugiyama International Conference on Artificial Intelligence and Statistics, 2618-2640, 2022 | | 2022 |
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
