| 2024 | ICPR | R-LIME: Rectangular Constraints and Optimization for Local Interpretable Model-agnostic Explanation Methods. | Genji Ohara, Keigo Kimura, Mineichi Kudo |
| 2023 | ECAI | Structured Sparse Multi-Task Learning with Generalized Group Lasso. | Luhuan Fei, Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2023 | ICDM | Multi-Label Personalized Classification via Exclusive Sparse Tensor Factorization. | Weijia Lin, Jiankun Wang, Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2023 | PRICAI | Incomplete Multi-view Weak-Label Learning with Noisy Features and Imbalanced Labels. | Zhiwei Li, Zijian Yang, Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2023 | PRICAI | Partial Multi-label Learning with a Few Accurately Labeled Data. | Haruhi Mizuguchi, Keigo Kimura, Mineichi Kudo, Lu Sun |
| 2022 | ICPR | Sensor Data Simulation with Wandering Behavior for the Elderly Living Alone. | Kai Tanaka, Mineichi Kudo, Keigo Kimura |
| 2022 | SSPR | Retargeted Regression Methods for Multi-label Learning. | Keigo Kimura, Jiaqi Bao, Mineichi Kudo, Lu Sun |
| 2022 | SSPR | Efficient Leave-One-Out Evaluation of Kernelized Implicit Mappings. | Mineichi Kudo, Keigo Kimura, Shumpei Morishita, Lu Sun |
| 2022 | SSPR | Realization of Autoencoders by Kernel Methods. | Shumpei Morishita, Mineichi Kudo, Keigo Kimura, Lu Sun |
| 2016 | ECAI | A Scalable Clustering-Based Local Multi-Label Classification Method. | Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2016 | ICPR | Fast random k-labELsets for large-scale multi-label classification. | Keigo Kimura, Mineichi Kudo, Lu Sun, Sadamori Koujaku |
| 2016 | ICPR | Simultaneous visualization of samples, features and multi-labels. | Mineichi Kudo, Keigo Kimura, Michal Haindl, Hiroshi Tenmoto |
| 2016 | ICPR | Locality in multi-label classification problems. | Batzaya Norov-Erdene, Mineichi Kudo, Lu Sun, Keigo Kimura |
| 2016 | ICPR | Multi-label classification with meta-label-specific features. | Lu Sun, Mineichi Kudo, Keigo Kimura |
| 2016 | SSPR | Simultaneous Nonlinear Label-Instance Embedding for Multi-label Classification. | Keigo Kimura, Mineichi Kudo, Lu Sun |
| 2015 | ICDM | Variable Selection for Efficient Nonnegative Tensor Factorization. | Keigo Kimura, Mineichi Kudo |
| 2014 | ACML | A Fast Hierarchical Alternating Least Squares Algorithm for Orthogonal Nonnegative Matrix Factorization. | Keigo Kimura, Yuzuru Tanaka, Mineichi Kudo |
| 2011 | GRC | Non-negative Matrix Factorization with sparse features. | Keigo Kimura, Tetsuya Yoshida |
| 2011 | GRC | Topic graph based transfer learning via generalized KL divergence based NMF. | Keigo Kimura, Tetsuya Yoshida |