| Multi-label classification with meta-label-specific features L Sun, M Kudo, K Kimura 2016 23rd International conference on pattern recognition (ICPR), 1612-1617, 2016 | 41 | 2016 |
| Fast random k-labelsets for large-scale multi-label classification K Kimura, M Kudo, L Sun, S Koujaku 2016 23rd International Conference on Pattern Recognition (ICPR), 438-443, 2016 | 19 | 2016 |
| Mlc toolbox: A matlab/octave library for multi-label classification K Kimura, L Sun, M Kudo arXiv preprint arXiv:1704.02592, 2017 | 16 | 2017 |
| Optimization of classifier chains via conditional likelihood maximization L Sun, M Kudo Pattern Recognition 74, 503-517, 2018 | 15 | 2018 |
| READER: robust semi-supervised multi-label dimension reduction L Sun, M Kudo, K Kimura IEICE TRANSACTIONS on Information and Systems 100 (10), 2597-2604, 2017 | 13 | 2017 |
| Simultaneous nonlinear label-instance embedding for multi-label classification K Kimura, M Kudo, L Sun Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016 | 12 | 2016 |
| Polytree-augmented classifier chains for multi-label classification L Sun, M Kudo Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 11 | 2015 |
| Multi-label classification by polytree-augmented classifier chains with label-dependent features L Sun, M Kudo Pattern analysis and applications 22, 1029-1049, 2019 | 10 | 2019 |
| A Scalable Clustering-Based Local Multi-Label Classification Method. L Sun, M Kudo, K Kimura ECAI, 261-268, 2016 | 10 | 2016 |
| Multi-Task Personalized Learning with Sparse Network Lasso. J Wang, L Sun IJCAI, 3516-3522, 2022 | 5 | 2022 |
| Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning. L Sun, CH Nguyen, H Mamitsuka IJCAI, 3506-3512, 2019 | 5 | 2019 |
| Dimension reduction using nonnegative matrix tri-factorization in multi-label classification K Kimura, M Kudo, L Sun Proceedings of the international conference on parallel and distributed …, 2015 | 5 | 2015 |
| Robust embedding regression for semi-supervised learning J Bao, M Kudo, K Kimura, L Sun Pattern Recognition 145, 109894, 2024 | 3 | 2024 |
| Fast and Robust Multi-View Multi-Task Learning via Group Sparsity. L Sun, CH Nguyen, H Mamitsuka IJCAI, 3499-3505, 2019 | 3 | 2019 |
| Locality in multi-label classification problems B Norov-Erdene, M Kudo, L Sun, K Kimura 2016 23rd International Conference on Pattern Recognition (ICPR), 2319-2324, 2016 | 2 | 2016 |
| Redirected transfer learning for robust multi-layer subspace learning J Bao, M Kudo, K Kimura, L Sun Pattern Analysis and Applications 27 (1), 1-19, 2024 | 1 | 2024 |
| Multi-Label Personalized Classification via Exclusive Sparse Tensor Factorization W Lin, J Wang, L Sun, M Kudo, K Kimura 2023 IEEE International Conference on Data Mining (ICDM), 398-407, 2023 | 1 | 2023 |
| Efficient Leave-One-Out Evaluation of Kernelized Implicit Mappings M Kudo, K Kimura, S Morishita, L Sun Joint IAPR International Workshops on Statistical Techniques in Pattern …, 2022 | 1 | 2022 |
| Multi-View Multi-Label Personalized Classification via Generalized Exclusive Sparse Tensor Factorization L Fei, W Lin, J Wang, L Sun, M Kudo, K Kimura | | 2024 |
| Partial Multi-label Learning with a Few Accurately Labeled Data H Mizuguchi, K Kimura, M Kudo, L Sun Pacific Rim International Conference on Artificial Intelligence, 79-90, 2023 | | 2023 |
Mineichi KudoProfessor of Computer Science, Hokkaido UniversityVerified email at ist.hokudai.ac.jp
