| 2025 | IJCNN | Online Learning Approach for Rough Set C-Means Clustering Using Nodes Approximating the Data Distribution. | Seiki Ubukata, Ryoga Hanafusa, Katsuhiro Honda |
| 2025 | KES | Comparative Study on Influences of False Negative Ratings in Collaborative Filtering with Fuzzy Co-Clustering. | Katsuhiro Honda, Jun-Seo Lee, Seiki Ubukata, Akira Notsu |
| 2024 | ICMLC | Spherical Rough C-Means Clustering and Its Application to Collaborative Filtering. | Seiki Ubukata, Daiki Io, Katsuhiro Honda |
| 2024 | ICMLC | Federated Rough C-Means Clustering and Its Application to Collaborative Filtering. | Seiki Ubukata, Shuichiro Yamashita, Katsuhiro Honda |
| 2024 | IJCNN | FCM-Induced Switching Reinforcement Learning for Collaborative Learning. | Katsuhiro Honda, Taimu Yaotome, Seiki Ubukata, Akira Notsu |
| 2022 | IJCNN | A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification. | Katsuhiro Honda, Koki Kitamori, Seiki Ubukata, Akira Notsu |
| 2021 | EUSFLAT | Fuzzy Clustering-based Switching Non-negative Matrix Factorization and Its Application to Environmental Data Analysis. | Katsuhiro Honda, T. Furukawa, Seiki Ubukata, Akira Notsu |
| 2021 | KES | Fuzzy | Katsuhiro Honda, Kohei Kunisawa, Seiki Ubukata, Akira Notsu |
| 2020 | CEC | Proposal of Adaptive Randomness in Differential Evolution. | Junya Tsubamoto, Akira Notsu, Seiki Ubukata, Katsuhiro Honda |
| 2018 | MDAI | Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data. | Katsuhiro Honda, Shotaro Matsuzaki, Seiki Ubukata, Akira Notsu |
| 2018 | SMC | Optimization of Learning Cycles in Online Reinforcement Learning Systems. | Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda |
| 2017 | IFSA | Visual assessment of co-cluster structure through cooccurrence-sensitive ordering. | Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu |
| 2017 | IFSA | A novel approach to noise clustering in multivariate fuzzy c-Means. | Katsuhiro Honda, Seiki Ubukata, Akira Notsu |
| 2017 | IFSA | Possibilistic co-clustering based on extension of noise rejection scheme in FCCMM. | Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda |
| 2016 | IJCNN | MMMs-induced k-member co-clustering for k-anonymization of cooccurrence information. | Katsuhiro Honda, Hikaru Sakamoto, Seiki Ubukata, Akira Notsu |
| 2015 | ICMLA | Performance Investigation of UCB Policy in Q-learning. | Koki Saito, Akira Notsu, Seiki Ubukata, Katsuhiro Honda |
| 2011 | GRC | Agents' KANSEI expression based on variable neighborhood models. | Seiki Ubukata, Tetsuya Murai, Yasuo Kudo |
| 2010 | GRC | A Multi-agent System Based on Variable Neighborhood Model. | Seiki Ubukata, Yasuo Kudo, Tetsuya Murai |
| 2009 | KES | An Agent Control Method Based on Variable Neighborhoods. | Seiki Ubukata, Yasuo Kudo, Tetsuya Murai |