Seiki Ubukata

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 64

Top Topics

Collaborative Filtering

Latent Semantic

Fuzzy Clustering

Cluster Validation

Top Venues

J. Adv. Comput. Intell. Intell. Informatics

Publications

Seiki Ubukata, Kazuma Ehara
Collaborative Filtering Based on Probabilistic Rough Set C-Means Clustering. IUKM (2) (2023)
Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A comparative study on effects of some exclusive conditions in fuzzy co-clustering for collaborative filtering. J. Ambient Intell. Humaniz. Comput. 14 (11) (2023)
Seiki Ubukata, Kazushi Futakuchi
Collaborative Filtering Based on Rough C-Means Clustering with Missing Value Processing. IUKM (2) (2023)
Katsuhiro Honda, Ryuta Kurahashi, Seiki Ubukata, Akira Notsu
Handling of Component-Wise Noise in ANFIS Induced by Ellipsoidal Fuzzy Clustering. FUZZ (2023)
Rikuto Daido, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
FCM-Induced Switching Fuzzy Factorization Machine for Collaborative Filtering. FUZZ (2023)
Seiki Ubukata, Kenryu Mouri, Katsuhiro Honda
Basic Consideration of Collaborative Filtering Based on Rough Co-clustering Induced by Multinomial Mixture Models. SCIS/ISIS (2022)
Kohei Kunisawa, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Fuzzy c-Lines for Vertically Distributed Database with Missing Values. SCIS/ISIS (2022)
Seiki Ubukata, Tomohiro Kawakami, Katsuhiro Honda
Adaptive Online Rough C-Means Clustering and Its Application to Collaborative Filtering. SSCI (2022)
Katsuhiro Honda, Satoshi Hyakutake, Seiki Ubukata, Akira Notsu
Handling of Missing Values in FCM Clustering-based ANFIS with Partial Distance Strategy. SCIS/ISIS (2022)
Katsuhiro Honda, Koki Kitamori, Seiki Ubukata, Akira Notsu
A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification. IJCNN (2022)
Yusuke Takahata, Katsuhiro Honda, Seiki Ubukata
A Comparative Study on Utilization of Semantic Information in Fuzzy Co-clustering. IUKM (2022)
Akira Okabe, Katsuhiro Honda, Seiki Ubukata
Noise Fuzzy Clustering-Based Robust Non-negative Matrix Factorization with I-divergence Criterion. IUKM (2022)
Katsuhiro Honda, Kosuke Hayashi, Seiki Ubukata, Akira Notsu
Fuzzy-Possibilistic Clustering for Categorical Multivariate Data. SICE (2021)
Katsuhiro Honda, Kohei Kunisawa, Seiki Ubukata, Akira Notsu
-Varieties Clustering for Vertically Distributed Datasets. KES (2021)
Seiki Ubukata, Akira Notsu, Katsuhiro Honda
Objective function-based rough membership C-means clustering. Inf. Sci. 548 (2021)
Katsuhiro Honda, Issei Hayashi, Seiki Ubukata, Akira Notsu
Three-Mode Fuzzy Co-Clustering Based on Probabilistic Concept and Comparison with FCM-Type Algorithms. J. Adv. Comput. Intell. Intell. Informatics 25 (4) (2021)
Seiki Ubukata, Shu Takahashi, Akira Notsu, Katsuhiro Honda
Basic Consideration of Collaborative Filtering Based on Rough C-Means Clustering. SCIS/ISIS (2020)
Seiki Ubukata, Narihira Nodake, Akira Notsu, Katsuhiro Honda
Basic Consideration of Co-Clustering Based on Rough Set Theory. IUKM (2020)
Seiki Ubukata, Sho Sekiya, Akira Notsu, Katsuhiro Honda
-Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 24 (6) (2020)
Seiki Ubukata, Atsushi Sugimoto, Akira Notsu, Katsuhiro Honda
Basic Consideration of Rough C-Medoids Clustering with Minkowski Distance. SCIS/ISIS (2020)
Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda
Online state space generation by a growing self-organizing map and differential learning for reinforcement learning. Appl. Soft Comput. 97 (Part B) (2020)
Junya Tsubamoto, Akira Notsu, Seiki Ubukata, Katsuhiro Honda
Proposal of Adaptive Randomness in Differential Evolution. CEC (2020)
Katsuhiro Honda, Keita Hoshii, Seiki Ubukata, Akira Notsu
A Noise Rejection Mechanism for pLSA-induced Fuzzy Co-clustering. FUZZ-IEEE (2020)
Katsuhiro Honda, Yoshiki Hakui, Seiki Ubukata, Akira Notsu
A Heuristic-Based Model for MMMs-Induced Fuzzy Co-Clustering with Dual Exclusive Partition. J. Adv. Comput. Intell. Intell. Informatics 24 (1) (2020)
Akira Notsu, Junya Tsubamoto, Yuichi Miyahira, Seiki Ubukata, Katsuhiro Honda
Randomness Selection in Differential Evolution Using Thompson Sampling. SCIS/ISIS (2020)
Katsuhiro Honda, Issei Hayashi, Seiki Ubukata, Akira Notsu
A Comparative Study on Three-mode Fuzzy Co-clustering Based on Co-occurrence Aggregation Criteria. CcS (2020)
Masaya Sakakibara, Akira Notsu, Seiki Ubukata, Katsuhiro Honda
Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation. J. Adv. Comput. Intell. Intell. Informatics 23 (4) (2019)
Ruixin Yang, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A Comparative Study on Questionnaire Design for Categorization Based on Fuzzy Co-clustering Concept and Multi-view Possibilistic Partition. iFUZZY (2019)
Masaaki Ueno, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Robust Non-negative Matrix Factorization Based on Noise Fuzzy Clustering Mechanism. AICCC (2019)
Keiko Kida, Seiki Ubukata, Akira Notsu, Katsuhiro Honda
Comparison of Gradient Descent Methods in Online Fuzzy Co-clustering. iFUZZY (2019)
Katsuhiro Honda, Ruixin Yang, Seiki Ubukata, Akira Notsu
Fuzzy Co-clustering for Categorization of Subjects in Questionnaire Considering Responsibility of Each Question. IUKM (2019)
Seiki Ubukata
A unified approach for cluster-wise and general noise rejection approaches for k-means clustering. PeerJ Comput. Sci. 5 (2019)
Takeaki Shimizu, Seiki Ubukata, Akira Notsu, Katsuhiro Honda
Effects of Semi-supervised Learning on Rough Membership C- Means Clustering. iFUZZY (2019)
Shinpei Nasada, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Fuzzy c-Regression Models with Cluster Characteristics Clarification. iFUZZY (2019)
Seiki Ubukata, Kazuki Yanagisawa, Akira Notsu, Katsuhiro Honda
Automatic Estimation of Cluster Number in Fuzzy Co-Clustering Based on Competition and Elimination of Clusters. SCIS&ISIS (2018)
Katsuhiro Honda, Shotaro Matsuzaki, Seiki Ubukata, Akira Notsu
Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data. MDAI (2018)
Seiki Ubukata, Takeaki Shimizu, Akira Notsu, Katsuhiro Honda
Effects of Semi-supervised Learning on Rough Set-Based C-Means Clustering. iFUZZY (2018)
Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu
Visual Co-Cluster Assessment with Intuitive Cluster Validation Through Cooccurrence-Sensitive Ordering. J. Adv. Comput. Intell. Intell. Informatics 22 (5) (2018)
Seiki Ubukata, Hiroki Kato, Akira Notsu, Katsuhiro Honda
Rough Set-Based Clustering Utilizing Probabilistic Memberships. J. Adv. Comput. Intell. Intell. Informatics 22 (6) (2018)
Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda
MMMs-Induced Possibilistic Fuzzy Co-Clustering and its Characteristics. J. Adv. Comput. Intell. Intell. Informatics 22 (5) (2018)
Seiki Ubukata, Akira Notsu, Keiko Kida, Katsuhiro Honda
Basic Consideration of Online and Mini-Batch Algorithms for MMMs-induced Fuzzy Co-clustering. iFUZZY (2018)
Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda
Optimization of Learning Cycles in Online Reinforcement Learning Systems. SMC (2018)
Seiki Ubukata, Keisuke Umado, Akira Notsu, Katsuhiro Honda
-Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 22 (4) (2018)
Akira Notsu, Masaya Sakakibara, Seiki Ubukata, Katsuhiro Honda
Setting of Candidate Solutions Considering Confidence Intervals in Differential Evolution. iFUZZY (2018)
Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Deterministic annealing process for pLSA-induced fuzzy co-clustering and cluster splitting characteristics. Int. J. Approx. Reason. 95 (2018)
Katsuhiro Honda, Yurina Suzuki, Mio Nishioka, Seiki Ubukata, Akira Notsu
A fuzzy co-clustering model for three-modes relational cooccurrence data. FUZZ-IEEE (2017)
Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu
FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK. Adv. Fuzzy Syst. 2017 (2017)
Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu
Noise Rejection in MMMs-Induced Fuzzy Co-Clustering. J. Adv. Comput. Intell. Intell. Informatics 21 (7) (2017)
Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda
Possibilistic co-clustering based on extension of noise rejection scheme in FCCMM. IFSA-SCIS (2017)
Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A novel approach to noise clustering in multivariate fuzzy c-Means. IFSA-SCIS (2017)
Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu
Visual assessment of co-cluster structure through cooccurrence-sensitive ordering. IFSA-SCIS (2017)
Nami Yamamoto, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Noise rejection schemes for FCM-type co-clustering based on uniform noise distribution. FUZZ-IEEE (2017)
Katsuhiro Honda, Takafumi Goshima, Seiki Ubukata, Akira Notsu
A fuzzy co-clustering interpretation of probabilistic latent semantic analysis. FUZZ-IEEE (2016)
Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A Semi-Supervised Framework for MMMs-Induced Fuzzy Co-Clustering with Virtual Samples. Adv. Fuzzy Syst. 2016 (2016)
Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A Study on Recommendation Ability in Collaborative Filtering by Fuzzy Co-Clustering with Exclusive Item Partition. SCIS&ISIS (2016)
Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced Fuzzy Co-clustering. IUKM (2016)
Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu
Cluster Validation in Multinomial Mixtures-Induced Fuzzy Co-Clustering. SCIS&ISIS (2016)
Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu
A Noise Fuzzy Co-Clustering Scheme in MMMs-Induced Clustering. SCIS&ISIS (2016)
Seiki Ubukata, Akira Notsu, Katsuhiro Honda
The Rough Set k-Means Clustering. SCIS&ISIS (2016)
Akira Notsu, Yuichi Hattori, Seiki Ubukata, Katsuhiro Honda
Visualization of Learning Process in "State and Action" Space Using Self-Organizing Maps. J. Adv. Comput. Intell. Intell. Informatics 20 (6) (2016)
Akira Notsu, Satoshi Kane, Seiki Ubukata, Katsuhiro Honda
Application of the UCT Algorithm for Noisy Optimization Problems. SCIS&ISIS (2016)
Katsuhiro Honda, Hikaru Sakamoto, Seiki Ubukata, Akira Notsu
MMMs-induced k-member co-clustering for k-anonymization of cooccurrence information. IJCNN (2016)
Seiki Ubukata, Akira Notsu, Katsuhiro Honda
The Rough Membership k-Means Clustering. IUKM (2016)
Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Fuzzy DA Clustering-Based Improvement of Probabilistic Latent Semantic Analysis. IUKM (2016)
Masahiro Inuiguchi, Takuya Hamakawa, Seiki Ubukata
Imprecise Rules for Data Privacy. RSKT (2015)
Koki Saito, Akira Notsu, Seiki Ubukata, Katsuhiro Honda
Performance Investigation of UCB Policy in Q-learning. ICMLA (2015)
Akira Notsu, Takanori Ueno, Yuichi Hattori, Seiki Ubukata, Katsuhiro Honda
FCM-Type Co-clustering Transfer Reinforcement Learning for Non-Markov Processes. IUKM (2015)
Katsuhiro Honda, Masahiro Omori, Seiki Ubukata, Akira Notsu
A study on fuzzy clustering-based k-anonymization for privacy preserving crowd movement analysis with face recognition. SoCPaR (2015)
Toshiya Oda, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
Fuzzy co-clustering considering site-wise confidence of vertically partitioned cooccurrence data. TAAI (2015)
Shunnya Oshio, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A Deterministic Clustering Framework in MMMs-Induced Fuzzy Co-clustering. IUKM (2015)
Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
A study on fuzzy co-clustering with partial supervision and virtual samples. TAAI (2015)
Katsuhiro Honda, Takaya Nakano, Chi-Hyon Oh, Seiki Ubukata, Akira Notsu
Partially Exclusive Item Partition in MMMs-Induced Fuzzy Co-Clustering and its Effects in Collaborative Filtering. J. Adv. Comput. Intell. Intell. Informatics 19 (6) (2015)
Akira Notsu, Koki Saito, Yuhumi Nohara, Seiki Ubukata, Katsuhiro Honda
Proposal of Grid Area Search with UCB for Discrete Optimization Problem. IUKM (2015)
Seiki Ubukata, Taro Miyazaki, Akira Notsu, Katsuhiro Honda, Masahiro Inuiguchi
An Ensemble Learning Approach Based on Rough Set Preserving the Qualities of Approximations. IUKM (2015)
Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu
MMMs-Induced Fuzzy Co-clustering with Exclusive Partition Penalty on Selected Items. IUKM (2015)
Seiki Ubukata, Taro Miyazaki, Akira Notsu, Katsuhiro Honda, Masahiro Inuiguchi
An Ensemble Learning Approach Based on Missing-Valued Tables. RSFDGrC (2015)
Seiki Ubukata, Tetsuya Murai, Yasuo Kudo, Seiki Akama
Variable Neighborhood Model for Agent Control Introducing Accessibility Relations Between Agents with Linear Temporal Logic. J. Adv. Comput. Intell. Intell. Informatics 18 (6) (2014)
Seiki Ubukata, Yasuo Kudo, Tetsuya Murai
Autonomous agent control based on variable neighbourhoods. Int. J. Reason. based Intell. Syst. 3 (1) (2011)
Seiki Ubukata, Tetsuya Murai, Yasuo Kudo
Agents' KANSEI expression based on variable neighborhood models. GrC (2011)
Seiki Ubukata, Yasuo Kudo, Tetsuya Murai
A Multi-agent System Based on Variable Neighborhood Model. GrC (2010)
Tetsuya Murai, Seiki Ubukata, Yasuo Kudo, Seiki Akama, Sadaaki Miyamoto
Granularity and Approximation in Sequences, Multisets, and Sets in the Framework of Kripke Semantics. IUM (2010)
Seiki Ubukata, Yasuo Kudo, Tetsuya Murai
An Agent Control Method Based on Variable Neighborhoods. KES (2) (2009)