Seiki Ubukata

According to our database, Seiki Ubukata authored at least 83 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

FCM-Induced Switching Reinforcement Learning for Collaborative Learning.

Katsuhiro Honda, Taimu Yaotome, Seiki Ubukata, Akira Notsu

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

A comparative study on effects of some exclusive conditions in fuzzy co-clustering for collaborative filtering.

Katsuhiro Honda, Seiki Ubukata, Akira Notsu

J. Ambient Intell. Humaniz. Comput., 2023

Collaborative Filtering Based on Rough C-Means Clustering with Missing Value Processing.

Seiki Ubukata, Kazushi Futakuchi

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2023

Collaborative Filtering Based on Probabilistic Rough Set C-Means Clustering.

Seiki Ubukata, Kazuma Ehara

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2023

Handling of Component-Wise Noise in ANFIS Induced by Ellipsoidal Fuzzy Clustering.

Katsuhiro Honda, Ryuta Kurahashi, Seiki Ubukata, Akira Notsu

Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

FCM-Induced Switching Fuzzy Factorization Machine for Collaborative Filtering.

Rikuto Daido, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

2022

Adaptive Online Rough C-Means Clustering and Its Application to Collaborative Filtering.

Seiki Ubukata, Tomohiro Kawakami, Katsuhiro Honda

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

Basic Consideration of Collaborative Filtering Based on Rough Co-clustering Induced by Multinomial Mixture Models.

Seiki Ubukata, Kenryu Mouri, Katsuhiro Honda

Proceedings of the Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, 2022

Fuzzy c-Lines for Vertically Distributed Database with Missing Values.

Kohei Kunisawa, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, 2022

Handling of Missing Values in FCM Clustering-based ANFIS with Partial Distance Strategy.

Katsuhiro Honda, Satoshi Hyakutake, Seiki Ubukata, Akira Notsu

Proceedings of the Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, 2022

A Comparative Study on Utilization of Semantic Information in Fuzzy Co-clustering.

Yusuke Takahata, Katsuhiro Honda, Seiki Ubukata

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2022

Noise Fuzzy Clustering-Based Robust Non-negative Matrix Factorization with I-divergence Criterion.

Akira Okabe, Katsuhiro Honda, Seiki Ubukata

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2022

A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification.

Katsuhiro Honda, Koki Kitamori, Seiki Ubukata, Akira Notsu

Proceedings of the International Joint Conference on Neural Networks, 2022

2021

Three-Mode Fuzzy Co-Clustering Based on Probabilistic Concept and Comparison with FCM-Type Algorithms.

Katsuhiro Honda, Issei Hayashi, Seiki Ubukata, Akira Notsu

J. Adv. Comput. Intell. Intell. Informatics, 2021

Objective function-based rough membership C-means clustering.

Seiki Ubukata, Akira Notsu, Katsuhiro Honda

Inf. Sci., 2021

Fuzzy-Possibilistic Clustering for Categorical Multivariate Data.

Katsuhiro Honda, Kosuke Hayashi, Seiki Ubukata, Akira Notsu

Proceedings of the 60th Annual Conference of the Society of Instrument and Control Engineers of Japan, 2021

Fuzzy <i>c</i>-Varieties Clustering for Vertically Distributed Datasets.

Katsuhiro Honda, Kohei Kunisawa, Seiki Ubukata, Akira Notsu

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

2020

Noise Rejection Approaches for Various Rough Set-Based <i>C</i>-Means Clustering.

Seiki Ubukata, Sho Sekiya, Akira Notsu, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2020

A Heuristic-Based Model for MMMs-Induced Fuzzy Co-Clustering with Dual Exclusive Partition.

Katsuhiro Honda, Yoshiki Hakui, Seiki Ubukata, Akira Notsu

J. Adv. Comput. Intell. Intell. Informatics, 2020

Online state space generation by a growing self-organizing map and differential learning for reinforcement learning.

Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda

Appl. Soft Comput., 2020

Basic Consideration of Collaborative Filtering Based on Rough C-Means Clustering.

Seiki Ubukata, Shu Takahashi, Akira Notsu, Katsuhiro Honda

Proceedings of the Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, 2020

Basic Consideration of Rough C-Medoids Clustering with Minkowski Distance.

Seiki Ubukata, Atsushi Sugimoto, Akira Notsu, Katsuhiro Honda

Proceedings of the Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, 2020

Randomness Selection in Differential Evolution Using Thompson Sampling.

Akira Notsu, Junya Tsubamoto, Yuichi Miyahira, Seiki Ubukata, Katsuhiro Honda

Proceedings of the Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems, 2020

Basic Consideration of Co-Clustering Based on Rough Set Theory.

Seiki Ubukata, Narihira Nodake, Akira Notsu, Katsuhiro Honda

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2020

A Noise Rejection Mechanism for pLSA-induced Fuzzy Co-clustering.

Katsuhiro Honda, Keita Hoshii, Seiki Ubukata, Akira Notsu

Proceedings of the 29th IEEE International Conference on Fuzzy Systems, 2020

Proposal of Adaptive Randomness in Differential Evolution.

Junya Tsubamoto, Akira Notsu, Seiki Ubukata, Katsuhiro Honda

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

A Comparative Study on Three-mode Fuzzy Co-clustering Based on Co-occurrence Aggregation Criteria.

Katsuhiro Honda, Issei Hayashi, Seiki Ubukata, Akira Notsu

Proceedings of the International Symposium on Community-centric Systems, 2020

2019

A unified approach for cluster-wise and general noise rejection approaches for k-means clustering.

Seiki Ubukata

PeerJ Comput. Sci., 2019

Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation.

Masaya Sakakibara, Akira Notsu, Seiki Ubukata, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2019

Fuzzy Co-clustering for Categorization of Subjects in Questionnaire Considering Responsibility of Each Question.

Katsuhiro Honda, Ruixin Yang, Seiki Ubukata, Akira Notsu

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2019

A Comparative Study on Questionnaire Design for Categorization Based on Fuzzy Co-clustering Concept and Multi-view Possibilistic Partition.

Ruixin Yang, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2019

Effects of Semi-supervised Learning on Rough Membership C- Means Clustering.

Takeaki Shimizu, Seiki Ubukata, Akira Notsu, Katsuhiro Honda

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2019

Fuzzy c-Regression Models with Cluster Characteristics Clarification.

Shinpei Nasada, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2019

Comparison of Gradient Descent Methods in Online Fuzzy Co-clustering.

Keiko Kida, Seiki Ubukata, Akira Notsu, Katsuhiro Honda

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2019

Robust Non-negative Matrix Factorization Based on Noise Fuzzy Clustering Mechanism.

Masaaki Ueno, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the AICCC 2019: 2nd Artificial Intelligence and Cloud Computing Conference, 2019

2018

Characteristics of Rough Set <i>C</i>-Means Clustering.

Seiki Ubukata, Keisuke Umado, Akira Notsu, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2018

Rough Set-Based Clustering Utilizing Probabilistic Memberships.

Seiki Ubukata, Hiroki Kato, Akira Notsu, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2018

MMMs-Induced Possibilistic Fuzzy Co-Clustering and its Characteristics.

Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2018

Visual Co-Cluster Assessment with Intuitive Cluster Validation Through Cooccurrence-Sensitive Ordering.

Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu

J. Adv. Comput. Intell. Intell. Informatics, 2018

Deterministic annealing process for pLSA-induced fuzzy co-clustering and cluster splitting characteristics.

Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Int. J. Approx. Reason., 2018

Optimization of Learning Cycles in Online Reinforcement Learning Systems.

Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Automatic Estimation of Cluster Number in Fuzzy Co-Clustering Based on Competition and Elimination of Clusters.

Seiki Ubukata, Kazuki Yanagisawa, Akira Notsu, Katsuhiro Honda

Proceedings of the 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2018

Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data.

Katsuhiro Honda, Shotaro Matsuzaki, Seiki Ubukata, Akira Notsu

Proceedings of the Modeling Decisions for Artificial Intelligence, 2018

Effects of Semi-supervised Learning on Rough Set-Based C-Means Clustering.

Seiki Ubukata, Takeaki Shimizu, Akira Notsu, Katsuhiro Honda

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2018

Basic Consideration of Online and Mini-Batch Algorithms for MMMs-induced Fuzzy Co-clustering.

Seiki Ubukata, Akira Notsu, Keiko Kida, Katsuhiro Honda

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2018

Setting of Candidate Solutions Considering Confidence Intervals in Differential Evolution.

Akira Notsu, Masaya Sakakibara, Seiki Ubukata, Katsuhiro Honda

Proceedings of the International Conference on Fuzzy Theory and Its Applications, 2018

2017

Noise Rejection in MMMs-Induced Fuzzy Co-Clustering.

Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu

J. Adv. Comput. Intell. Intell. Informatics, 2017

FCM-Type Fuzzy Coclustering for Three-Mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK.

Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu

Adv. Fuzzy Syst., 2017

Possibilistic co-clustering based on extension of noise rejection scheme in FCCMM.

Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda

Proceedings of the Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, 2017

A novel approach to noise clustering in multivariate fuzzy c-Means.

Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, 2017

Visual assessment of co-cluster structure through cooccurrence-sensitive ordering.

Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu

Proceedings of the Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, 2017

Noise rejection schemes for FCM-type co-clustering based on uniform noise distribution.

Nami Yamamoto, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017

A fuzzy co-clustering model for three-modes relational cooccurrence data.

Katsuhiro Honda, Yurina Suzuki, Mio Nishioka, Seiki Ubukata, Akira Notsu

Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017

2016

Visualization of Learning Process in "State and Action" Space Using Self-Organizing Maps.

Akira Notsu, Yuichi Hattori, Seiki Ubukata, Katsuhiro Honda

J. Adv. Comput. Intell. Intell. Informatics, 2016

A Semi-Supervised Framework for MMMs-Induced Fuzzy Co-Clustering with Virtual Samples.

Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Adv. Fuzzy Syst., 2016

The Rough Set k-Means Clustering.

Seiki Ubukata, Akira Notsu, Katsuhiro Honda

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

Application of the UCT Algorithm for Noisy Optimization Problems.

Akira Notsu, Satoshi Kane, Seiki Ubukata, Katsuhiro Honda

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

A Study on Recommendation Ability in Collaborative Filtering by Fuzzy Co-Clustering with Exclusive Item Partition.

Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

A Noise Fuzzy Co-Clustering Scheme in MMMs-Induced Clustering.

Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

Cluster Validation in Multinomial Mixtures-Induced Fuzzy Co-Clustering.

Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu

Proceedings of the 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Systems (ISIS), 2016

The Rough Membership k-Means Clustering.

Seiki Ubukata, Akira Notsu, Katsuhiro Honda

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced Fuzzy Co-clustering.

Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

Fuzzy DA Clustering-Based Improvement of Probabilistic Latent Semantic Analysis.

Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2016

MMMs-induced k-member co-clustering for k-anonymization of cooccurrence information.

Katsuhiro Honda, Hikaru Sakamoto, Seiki Ubukata, Akira Notsu

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

A fuzzy co-clustering interpretation of probabilistic latent semantic analysis.

Katsuhiro Honda, Takafumi Goshima, Seiki Ubukata, Akira Notsu

Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016

2015

Partially Exclusive Item Partition in MMMs-Induced Fuzzy Co-Clustering and its Effects in Collaborative Filtering.

Katsuhiro Honda, Takaya Nakano, Chi-Hyon Oh, Seiki Ubukata, Akira Notsu

J. Adv. Comput. Intell. Intell. Informatics, 2015

A study on fuzzy co-clustering with partial supervision and virtual samples.

Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

Fuzzy co-clustering considering site-wise confidence of vertically partitioned cooccurrence data.

Toshiya Oda, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2015

A study on fuzzy clustering-based k-anonymization for privacy preserving crowd movement analysis with face recognition.

Katsuhiro Honda, Masahiro Omori, Seiki Ubukata, Akira Notsu

Proceedings of the 7th International Conference of Soft Computing and Pattern Recognition, 2015

Imprecise Rules for Data Privacy.

Masahiro Inuiguchi, Takuya Hamakawa, Seiki Ubukata

Proceedings of the Rough Sets and Knowledge Technology - 10th International Conference, 2015

An Ensemble Learning Approach Based on Missing-Valued Tables.

Seiki Ubukata, Taro Miyazaki, Akira Notsu, Katsuhiro Honda, Masahiro Inuiguchi

Proceedings of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 2015

An Ensemble Learning Approach Based on Rough Set Preserving the Qualities of Approximations.

Seiki Ubukata, Taro Miyazaki, Akira Notsu, Katsuhiro Honda, Masahiro Inuiguchi

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2015

A Deterministic Clustering Framework in MMMs-Induced Fuzzy Co-clustering.

Shunnya Oshio, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2015

FCM-Type Co-clustering Transfer Reinforcement Learning for Non-Markov Processes.

Akira Notsu, Takanori Ueno, Yuichi Hattori, Seiki Ubukata, Katsuhiro Honda

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2015

Proposal of Grid Area Search with UCB for Discrete Optimization Problem.

Akira Notsu, Koki Saito, Yuhumi Nohara, Seiki Ubukata, Katsuhiro Honda

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2015

MMMs-Induced Fuzzy Co-clustering with Exclusive Partition Penalty on Selected Items.

Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2015

Performance Investigation of UCB Policy in Q-learning.

Koki Saito, Akira Notsu, Seiki Ubukata, Katsuhiro Honda

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2014

Variable Neighborhood Model for Agent Control Introducing Accessibility Relations Between Agents with Linear Temporal Logic.

Seiki Ubukata, Tetsuya Murai, Yasuo Kudo, Seiki Akama

J. Adv. Comput. Intell. Intell. Informatics, 2014

2011

Autonomous agent control based on variable neighbourhoods.

Seiki Ubukata, Yasuo Kudo, Tetsuya Murai

Int. J. Reason. based Intell. Syst., 2011

Agents' KANSEI expression based on variable neighborhood models.

Seiki Ubukata, Tetsuya Murai, Yasuo Kudo

Proceedings of the 2011 IEEE International Conference on Granular Computing, 2011

2010

Granularity and Approximation in Sequences, Multisets, and Sets in the Framework of Kripke Semantics.

Tetsuya Murai, Seiki Ubukata, Yasuo Kudo, Seiki Akama, Sadaaki Miyamoto

Proceedings of the Integrated Uncertainty Management and Applications [revised papers from the International Symposium on Integrated Uncertainty Management and Applications, 2010

A Multi-agent System Based on Variable Neighborhood Model.

Seiki Ubukata, Yasuo Kudo, Tetsuya Murai

Proceedings of the 2010 IEEE International Conference on Granular Computing, 2010

2009

An Agent Control Method Based on Variable Neighborhoods.

Seiki Ubukata, Yasuo Kudo, Tetsuya Murai

Proceedings of the Knowledge-Based and Intelligent Information and Engineering Systems, 2009