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2020 – today
- 2024
- [c166]Tomoya Matsuki, Akira Notsu, Katsuhiro Honda, Takuya Kato, Masakazu Shibahara:
Control of JADE Population in Limited Number of Searches for Realistic Situations. CEC 2024: 1-8 - [c165]Katsuhiro Honda, Taimu Yaotome, Seiki Ubukata, Akira Notsu:
FCM-Induced Switching Reinforcement Learning for Collaborative Learning. IJCNN 2024: 1-7 - 2023
- [j44]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): 14589-14594 (2023) - [c164]Rikuto Daido, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
FCM-Induced Switching Fuzzy Factorization Machine for Collaborative Filtering. FUZZ 2023: 1-6 - [c163]Katsuhiro Honda, Ryuta Kurahashi, Seiki Ubukata, Akira Notsu:
Handling of Component-Wise Noise in ANFIS Induced by Ellipsoidal Fuzzy Clustering. FUZZ 2023: 1-6 - [c162]Katsuhiro Honda, Ryosuke Amejima:
A Federated Learning Model for Linear Fuzzy Clustering with Least Square Criterion. IUKM (2) 2023: 15-24 - [c161]Kenta Nakaniwa, Tomoya Matsuki, Makishi Iguchi, Akira Notsu, Katsuhiro Honda:
Predicting Stock Price Fluctuations Considering the Sunny Effect. IUKM (2) 2023: 47-54 - [e3]Van-Nam Huynh, Bac Le, Katsuhiro Honda, Masahiro Inuiguchi, Youji Kohda:
Integrated Uncertainty in Knowledge Modelling and Decision Making - 10th International Symposium, IUKM 2023, Kanazawa, Japan, November 2-4, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14375, Springer 2023, ISBN 978-3-031-46774-5 [contents] - [e2]Katsuhiro Honda, Bac Le, Van-Nam Huynh, Masahiro Inuiguchi, Youji Kohda:
Integrated Uncertainty in Knowledge Modelling and Decision Making - 10th International Symposium, IUKM 2023, Kanazawa, Japan, November 2-4, 2023, Proceedings, Part II. Lecture Notes in Computer Science 14376, Springer 2023, ISBN 978-3-031-46780-6 [contents] - 2022
- [c160]Katsuhiro Honda, Koki Kitamori, Seiki Ubukata, Akira Notsu:
A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification. IJCNN 2022: 1-7 - [c159]Yusuke Takahata, Katsuhiro Honda, Seiki Ubukata:
A Comparative Study on Utilization of Semantic Information in Fuzzy Co-clustering. IUKM 2022: 216-225 - [c158]Akira Okabe, Katsuhiro Honda, Seiki Ubukata:
Noise Fuzzy Clustering-Based Robust Non-negative Matrix Factorization with I-divergence Criterion. IUKM 2022: 256-266 - [c157]Katsuhiro Honda, Satoshi Hyakutake, Seiki Ubukata, Akira Notsu:
Handling of Missing Values in FCM Clustering-based ANFIS with Partial Distance Strategy. SCIS/ISIS 2022: 1-6 - [c156]Kohei Kunisawa, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Fuzzy c-Lines for Vertically Distributed Database with Missing Values. SCIS/ISIS 2022: 1-6 - [c155]Seiki Ubukata, Kenryu Mouri, Katsuhiro Honda:
Basic Consideration of Collaborative Filtering Based on Rough Co-clustering Induced by Multinomial Mixture Models. SCIS/ISIS 2022: 1-6 - [c154]Seiki Ubukata, Tomohiro Kawakami, Katsuhiro Honda:
Adaptive Online Rough C-Means Clustering and Its Application to Collaborative Filtering. SSCI 2022: 368-373 - [e1]Katsuhiro Honda, Tomoe Entani, Seiki Ubukata, Van-Nam Huynh, Masahiro Inuiguchi:
Integrated Uncertainty in Knowledge Modelling and Decision Making - 9th International Symposium, IUKM 2022, Ishikawa, Japan, March 18-19, 2022, Proceedings. Lecture Notes in Computer Science 13199, Springer 2022, ISBN 978-3-030-98017-7 [contents] - 2021
- [j43]Seiki Ubukata, Akira Notsu, Katsuhiro Honda:
Objective function-based rough membership C-means clustering. Inf. Sci. 548: 479-496 (2021) - [j42]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): 478-488 (2021) - [c153]Katsuhiro Honda, Kohei Kunisawa, Seiki Ubukata, Akira Notsu:
Fuzzy c-Varieties Clustering for Vertically Distributed Datasets. KES 2021: 457-466 - [c152]Katsuhiro Honda, Kosuke Hayashi, Seiki Ubukata, Akira Notsu:
Fuzzy-Possibilistic Clustering for Categorical Multivariate Data. SICE 2021: 9-14 - 2020
- [j41]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): 106723 (2020) - [j40]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): 40-47 (2020) - [j39]Yasushi Nishida, Katsuhiro Honda:
Visualization of Potential Technical Solutions by SOM and Co-Clustering and its Extension to Multi-View Situation. J. Adv. Comput. Intell. Intell. Informatics 24(1): 65-72 (2020) - [j38]Seiki Ubukata, Sho Sekiya, Akira Notsu, Katsuhiro Honda:
Noise Rejection Approaches for Various Rough Set-Based C-Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 24(6): 738-749 (2020) - [c151]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: 1-6 - [c150]Junya Tsubamoto, Akira Notsu, Seiki Ubukata, Katsuhiro Honda:
Proposal of Adaptive Randomness in Differential Evolution. CEC 2020: 1-8 - [c149]Katsuhiro Honda, Keita Hoshii, Seiki Ubukata, Akira Notsu:
A Noise Rejection Mechanism for pLSA-induced Fuzzy Co-clustering. FUZZ-IEEE 2020: 1-8 - [c148]Seiki Ubukata, Narihira Nodake, Akira Notsu, Katsuhiro Honda:
Basic Consideration of Co-Clustering Based on Rough Set Theory. IUKM 2020: 151-161 - [c147]Yasushi Nishida, Katsuhiro Honda:
SOM-Based Visualization of Potential Technical Solutions with Fuzzy Bag-of-Words Utilizing Multi-view Information. IUKM 2020: 187-198 - [c146]Akira Notsu, Junya Tsubamoto, Yuichi Miyahira, Seiki Ubukata, Katsuhiro Honda:
Randomness Selection in Differential Evolution Using Thompson Sampling. SCIS/ISIS 2020: 1-5 - [c145]Seiki Ubukata, Atsushi Sugimoto, Akira Notsu, Katsuhiro Honda:
Basic Consideration of Rough C-Medoids Clustering with Minkowski Distance. SCIS/ISIS 2020: 1-6 - [c144]Seiki Ubukata, Shu Takahashi, Akira Notsu, Katsuhiro Honda:
Basic Consideration of Collaborative Filtering Based on Rough C-Means Clustering. SCIS/ISIS 2020: 1-6
2010 – 2019
- 2019
- [j37]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): 758-766 (2019) - [c143]Masaaki Ueno, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Robust Non-negative Matrix Factorization Based on Noise Fuzzy Clustering Mechanism. AICCC 2019: 1-5 - [c142]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: 1-4 - [c141]Shinpei Nasada, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Fuzzy c-Regression Models with Cluster Characteristics Clarification. iFUZZY 2019: 5-8 - [c140]Keiko Kida, Seiki Ubukata, Akira Notsu, Katsuhiro Honda:
Comparison of Gradient Descent Methods in Online Fuzzy Co-clustering. iFUZZY 2019: 9-14 - [c139]Takeaki Shimizu, Seiki Ubukata, Akira Notsu, Katsuhiro Honda:
Effects of Semi-supervised Learning on Rough Membership C- Means Clustering. iFUZZY 2019: 15-20 - [c138]Yasushi Nishida, Katsuhiro Honda:
A Comparative Study on SOM-Based Visualization of Potential Technical Solutions Using Fuzzy Bag-of-Words and Co-occurrence Probability of Technical Words. IUKM 2019: 360-369 - [c137]Katsuhiro Honda, Ruixin Yang, Seiki Ubukata, Akira Notsu:
Fuzzy Co-clustering for Categorization of Subjects in Questionnaire Considering Responsibility of Each Question. IUKM 2019: 370-379 - 2018
- [j36]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: 185-193 (2018) - [j35]Seiki Ubukata, Keisuke Umado, Akira Notsu, Katsuhiro Honda:
Characteristics of Rough Set C-Means Clustering. J. Adv. Comput. Intell. Intell. Informatics 22(4): 551-564 (2018) - [j34]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): 585-592 (2018) - [j33]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): 747-758 (2018) - [j32]Seiki Ubukata, Hiroki Kato, Akira Notsu, Katsuhiro Honda:
Rough Set-Based Clustering Utilizing Probabilistic Memberships. J. Adv. Comput. Intell. Intell. Informatics 22(6): 956-964 (2018) - [j31]Toly Chen, Katsuhiro Honda:
Solving data preprocessing problems in existing location-aware systems. J. Ambient Intell. Humaniz. Comput. 9(2): 253-259 (2018) - [c136]Akira Notsu, Masaya Sakakibara, Seiki Ubukata, Katsuhiro Honda:
Setting of Candidate Solutions Considering Confidence Intervals in Differential Evolution. iFUZZY 2018: 7-11 - [c135]Seiki Ubukata, Takeaki Shimizu, Akira Notsu, Katsuhiro Honda:
Effects of Semi-supervised Learning on Rough Set-Based C-Means Clustering. iFUZZY 2018: 12-17 - [c134]Seiki Ubukata, Akira Notsu, Keiko Kida, Katsuhiro Honda:
Basic Consideration of Online and Mini-Batch Algorithms for MMMs-induced Fuzzy Co-clustering. iFUZZY 2018: 85-90 - [c133]Katsuhiro Honda, Shotaro Matsuzaki, Seiki Ubukata, Akira Notsu:
Privacy Preserving Collaborative Fuzzy Co-clustering of Three-Mode Cooccurrence Data. MDAI 2018: 232-242 - [c132]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: 660-665 - [c131]Yasushi Nishida, Katsuhiro Honda:
Visualization of Potential Technical Solutions by Self-Organizing Maps and Co-Cluster Extraction. SCIS&ISIS 2018: 820-825 - [c130]Akira Notsu, Koji Yasuda, Seiki Ubukata, Katsuhiro Honda:
Optimization of Learning Cycles in Online Reinforcement Learning Systems. SMC 2018: 3530-3534 - 2017
- [j30]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: 9842127:1-9842127:8 (2017) - [j29]Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu:
Noise Rejection in MMMs-Induced Fuzzy Co-Clustering. J. Adv. Comput. Intell. Intell. Informatics 21(7): 1144-1151 (2017) - [c129]Katsuhiro Honda:
Fuzzy Clustering/Co-clustering and Probabilistic Mixture Models-Induced Algorithms. Fuzzy Sets, Rough Sets, Multisets and Clustering 2017: 29-43 - [c128]Katsuhiro Honda, Yurina Suzuki, Mio Nishioka, Seiki Ubukata, Akira Notsu:
A fuzzy co-clustering model for three-modes relational cooccurrence data. FUZZ-IEEE 2017: 1-6 - [c127]Nami Yamamoto, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Noise rejection schemes for FCM-type co-clustering based on uniform noise distribution. FUZZ-IEEE 2017: 1-6 - [c126]Katsuhiro Honda, Takuya Sako, Seiki Ubukata, Akira Notsu:
Visual assessment of co-cluster structure through cooccurrence-sensitive ordering. IFSA-SCIS 2017: 1-6 - [c125]Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
A novel approach to noise clustering in multivariate fuzzy c-Means. IFSA-SCIS 2017: 1-4 - [c124]Seiki Ubukata, Katsuya Koike, Akira Notsu, Katsuhiro Honda:
Possibilistic co-clustering based on extension of noise rejection scheme in FCCMM. IFSA-SCIS 2017: 1-6 - 2016
- [j28]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: 5206048:1-5206048:8 (2016) - [j27]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): 983-991 (2016) - [c123]Katsuhiro Honda, Takafumi Goshima, Seiki Ubukata, Akira Notsu:
A fuzzy co-clustering interpretation of probabilistic latent semantic analysis. FUZZ-IEEE 2016: 718-723 - [c122]Katsuhiro Honda, Hikaru Sakamoto, Seiki Ubukata, Akira Notsu:
MMMs-induced k-member co-clustering for k-anonymization of cooccurrence information. IJCNN 2016: 2961-2966 - [c121]Katsuhiro Honda:
Fuzzy Co-Clustering and Application to Collaborative Filtering. IUKM 2016: 16-23 - [c120]Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Fuzzy DA Clustering-Based Improvement of Probabilistic Latent Semantic Analysis. IUKM 2016: 175-184 - [c119]Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced Fuzzy Co-clustering. IUKM 2016: 185-194 - [c118]Seiki Ubukata, Akira Notsu, Katsuhiro Honda:
The Rough Membership k-Means Clustering. IUKM 2016: 207-216 - [c117]Akira Notsu, Satoshi Kane, Seiki Ubukata, Katsuhiro Honda:
Application of the UCT Algorithm for Noisy Optimization Problems. SCIS&ISIS 2016: 48-52 - [c116]Seiki Ubukata, Akira Notsu, Katsuhiro Honda:
The Rough Set k-Means Clustering. SCIS&ISIS 2016: 189-193 - [c115]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: 686-689 - [c114]Katsuhiro Honda, Yurina Suzuki, Seiki Ubukata, Akira Notsu:
Cluster Validation in Multinomial Mixtures-Induced Fuzzy Co-Clustering. SCIS&ISIS 2016: 690-694 - [c113]Katsuhiro Honda, Nami Yamamoto, Seiki Ubukata, Akira Notsu:
A Noise Fuzzy Co-Clustering Scheme in MMMs-Induced Clustering. SCIS&ISIS 2016: 695-699 - 2015
- [j26]Katsuhiro Honda, Toshiya Oda, Daiji Tanaka, Akira Notsu:
A Collaborative Framework for Privacy Preserving Fuzzy Co-Clustering of Vertically Distributed Cooccurrence Matrices. Adv. Fuzzy Syst. 2015 (2015) - [j25]Katsuhiro Honda, Shunnya Oshio, Akira Notsu:
Fuzzy Co-Clustering Induced by Multinomial Mixture Models. J. Adv. Comput. Intell. Intell. Informatics 19(6): 717-726 (2015) - [j24]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): 810-817 (2015) - [c112]Koki Saito, Akira Notsu, Seiki Ubukata, Katsuhiro Honda:
Performance Investigation of UCB Policy in Q-learning. ICMLA 2015: 777-780 - [c111]Akira Notsu, Koki Saito, Yuhumi Nohara, Seiki Ubukata, Katsuhiro Honda:
Proposal of Grid Area Search with UCB for Discrete Optimization Problem. IUKM 2015: 102-111 - [c110]Shunnya Oshio, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
A Deterministic Clustering Framework in MMMs-Induced Fuzzy Co-clustering. IUKM 2015: 204-213 - [c109]Akira Notsu, Takanori Ueno, Yuichi Hattori, Seiki Ubukata, Katsuhiro Honda:
FCM-Type Co-clustering Transfer Reinforcement Learning for Non-Markov Processes. IUKM 2015: 214-225 - [c108]Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
MMMs-Induced Fuzzy Co-clustering with Exclusive Partition Penalty on Selected Items. IUKM 2015: 226-235 - [c107]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: 247-253 - [c106]Seiki Ubukata, Taro Miyazaki, Akira Notsu, Katsuhiro Honda, Masahiro Inuiguchi:
An Ensemble Learning Approach Based on Missing-Valued Tables. RSFDGrC 2015: 310-321 - [c105]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: 37-41 - [c104]Toshiya Oda, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
Fuzzy co-clustering considering site-wise confidence of vertically partitioned cooccurrence data. TAAI 2015: 404-407 - [c103]Daiji Tanaka, Katsuhiro Honda, Seiki Ubukata, Akira Notsu:
A study on fuzzy co-clustering with partial supervision and virtual samples. TAAI 2015: 408-411 - 2014
- [j23]Arina Kawano, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Performance Comparison of Collaborative Filtering with k-Anonymized Data by Fuzzy k-Member Clustering. J. Adv. Comput. Intell. Intell. Informatics 18(2): 239-245 (2014) - [j22]Toshiro Ogita, Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda:
Improvement of PCA-Based Approximate Nearest Neighbor Search Using Distance Statistics. J. Adv. Comput. Intell. Intell. Informatics 18(4): 658-664 (2014) - [c102]Katsuhiro Honda, Daiji Tanaka, Akira Notsu:
Incremental algorithms for fuzzy co-clustering of very large cooccurrence matrix. FUZZ-IEEE 2014: 2494-2499 - [c101]Katsuhiro Honda, Toshiya Oda, Akira Notsu:
Fuzzy co-clustering of vertically partitioned cooccurrence data with privacy consideration. FUZZ-IEEE 2014: 2500-2504 - [c100]Katsuhiro Honda, Shunnya Oshio, Akira Notsu:
FCM-type fuzzy co-clustering by K-L information regularization. FUZZ-IEEE 2014: 2505-2510 - [c99]Katsuhiro Honda, Shunnya Oshio, Akira Notsu:
Item membership fuzzification in fuzzy co-clustering based on multinomial mixture concept. GrC 2014: 94-99 - [c98]Mai Muranishi, Katsuhiro Honda, Akira Notsu:
Application of xie-beni-type validity index to fuzzy co-clustering models based on cluster aggregation and pseudo-cluster-center estimation. ISDA 2014: 34-38 - [c97]Shunsuke Iwata, Katsuhiro Honda, Akira Notsu:
Alternative fuzzy c-regression models with tolerance. SCIS&ISIS 2014: 501-505 - [c96]Akira Suwa, Katsuhiro Honda, Akira Notsu, Tomoe Entani:
A comparative study on clustering-based group scenario summarization in AHP. SCIS&ISIS 2014: 688-693 - [c95]Daiji Tanaka, Toshiya Oda, Katsuhiro Honda, Akira Notsu:
Privacy preserving fuzzy co-clustering with distributed cooccurrence matrices. SCIS&ISIS 2014: 700-705 - [c94]Koki Saito, Akira Notsu, Katsuhiro Honda:
Discounted UCB1-tuned for Q-learning. SCIS&ISIS 2014: 966-970 - [c93]Yuichi Hattori, Akira Notsu, Katsuhiro Honda:
Epidemie process simulator by multi agent simulation considering urban models. SCIS&ISIS 2014: 1403-1407 - [c92]Katsuhiro Honda, Chi-Hyon Oh, Akira Notsu:
Exclusive condition on item partition in fuzzy co-clustering based on K-L information regularization. SCIS&ISIS 2014: 1413-1417 - [c91]Yuki Tezuka, Akira Notsu, Katsuhiro Honda:
Utility of Turning Spot Learning under complex goal search and the limit of memory usage. SCIS&ISIS 2014: 1418-1423 - [p3]Katsuhiro Honda, Akira Notsu, Chi-Hyon Oh:
Handling Very Large Cooccurrence Matrices in Fuzzy Co-clustering by Sampling Approaches. Soft Computing in Artificial Intelligence 2014: 19-27 - [p2]Mai Muranishi, Katsuhiro Honda, Akira Notsu:
Xie-Beni-Type Fuzzy Cluster Validation in Fuzzy Co-clustering of Documents and Keywords. Soft Computing in Artificial Intelligence 2014: 29-38 - [p1]Shunsuke Iwata, Katsuhiro Honda, Akira Notsu:
Fuzzy c-Regression Models Based on Optimal Scaling of Categorical Observation with Tolerance. Soft Computing in Artificial Intelligence 2014: 39-47 - 2013
- [j21]Katsuhiro Honda, Takeshi Yamamoto, Akira Notsu, Hidetomo Ichihashi:
Visualization of Non-Euclidean Relational Data by Robust Linear Fuzzy Clustering Based on FCMdd Framework. J. Adv. Comput. Intell. Intell. Informatics 17(2): 312-317 (2013) - [c90]Shunsuke Iwata, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Fuzzy c-Regression Models with direction-dependent uncertainty and its application to residential solar electric power analysis. FUZZ-IEEE 2013 - [c89]Hirohide Kasugai, Arina Kawano, Katsuhiro Honda, Akira Notsu:
A study on applicability of fuzzy k-member clustering to privacy preserving pattern recognition. FUZZ-IEEE 2013: 1-6 - [c88]Mai Muranishi, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
A cluster validity index for FCM-type co-clustering. FUZZ-IEEE 2013 - [c87]Akira Suwa, Katsuhiro Honda, Akira Notsu, Tomoe Entani:
Intrinsic scenario estimation by noise fuzzy clustering in group decision making. FUZZ-IEEE 2013: 1-6 - [c86]Takuya Kobayashi, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Applicability of ICA-Based Dimension Reduction in Fuzzy c-Means-Based Classifier. ICONIP (3) 2013: 93-100 - [c85]Arina Kawano, Katsuhiro Honda, Hirohide Kasugai, Akira Notsu:
A Greedy Algorithm for k-Member Co-clustering and its Applicability to Collaborative Filtering. KES 2013: 477-484 - [c84]Chi-Hyon Oh, Katsuhiro Honda:
Dual Exclusive Partition in Fuzzy CoDoK and SCAD-based Fuzzy Co-clustering. KES 2013: 800-809 - [c83]Akira Notsu, Hirokazu Kawakami, Yuki Tezuka, Katsuhiro Honda:
Intergration of Information based on the Similarity in AHP. KES 2013: 1011-1020 - [c82]Yuki Tezuka, Akira Notsu, Katsuhiro Honda:
Introduction of Majority Vote of Neighborhood Conditions for Sneak form Reinforcement Learning. KES 2013: 1021-1028 - 2012
- [j20]Yuki Komori, Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi:
Automatic Adaptive Space Segmentation for Reinforcement Learning. Int. J. Fuzzy Log. Intell. Syst. 12(1): 36-41 (2012) - [c81]Tomoe Entani, Katsuhiro Honda:
Group decision support by interval AHP with uncertainty-based hierarchical clustering. FUZZ-IEEE 2012: 1-6 - [c80]Katsuhiro Honda, Arina Kawano, Akira Notsu, Hidetomo Ichihashi:
A fuzzy variant of k-member clustering for collaborative filtering with data anonymization. FUZZ-IEEE 2012: 1-6 - [c79]Katsuhiro Honda, Sakuya Nakao, Akira Notsu, Hidetomo Ichihashi:
Alternative fuzzy c-lines and comparison with noise clustering in cluster validation. FUZZ-IEEE 2012: 1-6 - [c78]Hidetomo Ichihashi, Toshiro Ogita, Katsuhiro Honda, Akira Notsu:
Improvement by sorting and thresholding in PCA based nearest neighbor search. FUZZ-IEEE 2012: 1-6 - [c77]Yui Matsumoto, Takeshi Yamamoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Application of cluster validity criteria to Rock-Paper-Scissors game judgment. FUZZ-IEEE 2012: 1-5 - [c76]Katsuhiro Honda, Yui Matsumoto, Arina Kawano, Akira Notsu, Hidetomo Ichihashi:
A Study on Privacy Preserving Collaborative Filtering with Data Anonymization by Clustering. IIMSS 2012: 43-52 - [c75]Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi, Ayaka Ido, Yuki Komori:
Information compression effect based on PCA for reinforcement learning agents' communication. SCIS&ISIS 2012: 1318-1321 - [c74]Katsuhiro Honda, Chi-Hyon Oh, Akira Notsu, Hidetomo Ichihashi:
FCM-type co-clustering with exclusive partition of selected items and application to collaborative filtering. SCIS&ISIS 2012: 1327-1330 - [c73]Katsuhiro Honda, Shotaro Osaka, Akira Notsu, Hidetomo Ichihashi:
Template-based fuzzy clustering with cluster-wise coordinate transformation. SCIS&ISIS 2012: 1331-1334 - [c72]Tsuyoshi Beppu, Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi:
Reinforcement learning with particles for instant optimality. SCIS&ISIS 2012: 1528-1533 - [c71]Ryoichi Nonoguchi, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Cluster validation in k-Means clustering of mixed databases based on principal component analysis. SCIS&ISIS 2012: 1784-1789 - [c70]Sakuya Nakao, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Robust local subspace learning by linear fuzzy clustering with Alternative c-Means criterion. SCIS&ISIS 2012: 1790-1795 - [c69]Yui Matsumoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
FCM-type co-clustering of categorical multivariate data with exclusive partition. SCIS&ISIS 2012: 1796-1800 - [c68]Takuya Kobayashi, Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu:
Mixed usage of MATLAB and visual C for improving classification time and training time of FCM classifier. SCIS&ISIS 2012: 1994-1998 - [c67]Hidetomo Ichihashi, Toshiro Ogita, Akira Notsu, Katsuhiro Honda:
PCA-Tree NNS with two approximation methods and annulus bound method. SCIS&ISIS 2012: 1999-2003 - [c66]Arina Kawano, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Comparison on membership functions in fuzzy k-member clustering for data anonymization. SCIS&ISIS 2012: 2004-2008 - 2011
- [j19]Takeshi Yamamoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
A Comparative Study on TIBA Imputation Methods in FCMdd-Based Linear Clustering with Relational Data. Adv. Fuzzy Syst. 2011: 265170:1-265170:10 (2011) - [j18]Katsuhiro Honda, Akira Notsu, Tomohiro Matsui, Hidetomo Ichihashi:
Fuzzy Cluster Validation Based on Fuzzy PCA-Guided Procedure. Int. J. Fuzzy Syst. Appl. 1(1): 49-60 (2011) - [j17]Katsuhiro Honda, Sakuya Nakao, Akira Notsu, Hidetomo Ichihashi:
Alternative fuzzy c-lines and local principal component extraction. Int. J. Knowl. Eng. Soft Data Paradigms 3(2): 188-200 (2011) - [j16]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Variable Weighting in PCA-Guided k-Means and its Connection with Information Summarization. J. Adv. Comput. Intell. Intell. Informatics 15(1): 83-89 (2011) - [j15]Takeshi Yamamoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Non-Euclidean Extension of FCMdd-Based Linear Clustering for Relational Data. J. Adv. Comput. Intell. Intell. Informatics 15(8): 1050-1056 (2011) - [c65]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu:
Comparison of scaling behavior between fuzzy c-means based classifier with many parameters and LibSVM. FUZZ-IEEE 2011: 386-393 - [c64]Hidetomo Ichihashi, Li Chieu Lam, Katsuhiro Honda, Akira Notsu:
Ellipse detection with hard c-regression models and random initializations. FUZZ-IEEE 2011: 394-400 - [c63]Katsuhiro Honda, Yui Matsumoto, Akira Notsu, Hidetomo Ichihashi:
A study on regularization effects of fuzzified memberships in FCM clustering. FUZZ-IEEE 2011: 416-421 - [c62]Takeshi Yamamoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
FCMdd-type linear fuzzy clustering for incomplete non-Euclidean relational data. FUZZ-IEEE 2011: 792-798 - [c61]Daisuke Yoshida, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Hybrid objective function of Fuzzy c-Varieties and cross-shape fuzzy cluster extraction. FUZZ-IEEE 2011: 799-803 - [c60]Akira Notsu, Yuki Komori, Katsuhiro Honda, Hidetomo Ichihashi:
Influence of the space segmentation and its adaptive automation for reinforcement learning. FUZZ-IEEE 2011: 1079-1083 - [c59]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Partially exclusive condition for sequential fuzzy co-cluster extraction. FUZZ-IEEE 2011: 1695-1700 - [c58]Katsuhiro Honda, Ryoichi Nonoguchi, Akira Notsu, Hidetomo Ichihashi:
PCA-guided k-Means clustering with incomplete data. FUZZ-IEEE 2011: 1710-1714 - [c57]Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi:
Proposed particle-filtering method for reinforcement learning. FUZZ-IEEE 2011: 1755-1718 - [c56]Takeshi Yamamoto, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Robust FCMdd-based Linear Clustering for Relational Data with Alternative c-Means Criterion. ICMLA (2) 2011: 334-337 - [c55]Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi, Yuki Komori, Yuuki Iwamoto:
Improvement of Particle Filter for Reinforcement Learning. ICMLA (1) 2011: 454-457 - [c54]Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi, Yuki Komori:
Simple Reinforcement Learning for Small-Memory Agent. ICMLA (1) 2011: 458-461 - 2010
- [j14]Naoki Haga, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Local subspace learning by extended fuzzy c-medoids clustering. Int. J. Knowl. Eng. Soft Data Paradigms 2(2): 169-181 (2010) - [j13]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Collaborative filtering by sequential user-item co-cluster extraction from rectangular relational data. Int. J. Knowl. Eng. Soft Data Paradigms 2(4): 312-327 (2010) - [j12]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Fuzzy PCA-Guided Robust k -Means Clustering. IEEE Trans. Fuzzy Syst. 18(1): 67-79 (2010) - [c53]Katsuhiro Honda, Akira Notsu, Tomohiro Matsui, Hidetomo Ichihashi:
PCA-guided fuzzy cluster validation with noise rejection. FUZZ-IEEE 2010: 1-6 - [c52]Hidetomo Ichihashi, Tatsuya Katada, Makoto Fujiyoshi, Akira Notsu, Katsuhiro Honda:
Improvement in the performance of camera based vehicle detector for parking lot. FUZZ-IEEE 2010: 1-7 - [c51]Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda:
Semi-hard c-means clustering with application to classifier design. FUZZ-IEEE 2010: 1-8 - [c50]Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda:
Fuzzy and Semi-hard c-Means Clustering with Application to Classifier Design. IUM 2010: 465-476
2000 – 2009
- 2009
- [j11]Akira Notsu, Hidetomo Ichihashi, Katsuhiro Honda, Osamu Katai:
Visualization of balancing systems based on naïve psychological approaches. AI Soc. 23(2): 281-296 (2009) - [c49]Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda, Tatsuya Katada, Makoto Fujiyoshi:
Vacant parking space detector for outdoor parking lot by using surveillance camera and FCM classifier. FUZZ-IEEE 2009: 127-134 - [c48]Katsuhiro Honda, Tomonari Nomaguchi, Akira Notsu, Hidetomo Ichihashi:
A comparative study on cluster validity criteria in linear fuzzy clustering and pareto optimality analysis. FUZZ-IEEE 2009: 1101-1106 - [c47]Naoki Haga, Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Cluster validation in linear fuzzy clustering of relational data from multi-cluster principal coordinate analysis view point. FUZZ-IEEE 2009: 1131-1136 - [c46]Kazuya Nagaura, Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda:
Benchmarking parameterized fuzzy c-Means classifier. FUZZ-IEEE 2009: 1137-1144 - [c45]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
Collaborative filtering by sequential extraction of user-item clusters based on structural balancing approach. FUZZ-IEEE 2009: 1540-1545 - [c44]Tomohiro Matsui, Katsuhiro Honda, Chi-Hyon Oh, Akira Notsu, Hidetomo Ichihashi:
Cluster validation in k-Means clustering based on PCA-guided k-Means and procrustean transformation of PC scores. FUZZ-IEEE 2009: 1546-1550 - [c43]Akira Notsu, Katsuhiro Honda, Hidetomo Ichihashi:
Conceptual graph generation from text documents based on perceptual balance. FUZZ-IEEE 2009: 1551-1556 - [c42]Chi-Hyon Oh, Katsuhiro Honda, Hidetomo Ichihashi:
A fuzzy model-based community simulator for behavior analysis in virtual theme park. FUZZ-IEEE 2009: 1557-1562 - [c41]Shingo Aoki, Kazushige Inoue, Tomoharu Nakashima, Katsuhiro Honda:
Efficiency measurement for agent simulation based on DEA with imprecise data. FUZZ-IEEE 2009: 1563-1567 - [c40]Hidetomo Ichihashi, Akira Notsu, Katsuhiro Honda:
Triplet of FCM classifiers. FUZZ-IEEE 2009: 1826-1833 - [c39]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
PCA-Guided k-Means with Variable Weighting and Its Application to Document Clustering. MDAI 2009: 282-292 - 2008
- [b1]Sadaaki Miyamoto, Hidetomo Ichihashi, Katsuhiro Honda:
Algorithms for Fuzzy Clustering - Methods in c-Means Clustering with Applications. Studies in Fuzziness and Soft Computing 229, Springer 2008, ISBN 978-3-540-78736-5, pp. 1-233 [contents] - [c38]Yu Yamamoto, Akira Notsu, Hidetomo Ichihashi, Katsuhiro Honda:
Agent-based social simulation based on cognitive economic efficiency. IEEE Congress on Evolutionary Computation 2008: 1089-1094 - [c37]Katsuhiro Honda, Takahiro Ohyama, Hidetomo Ichihashi, Akira Notsu:
FCM-type switching regression with alternating least squares method. FUZZ-IEEE 2008: 122-127 - [c36]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Eri Miyamoto:
FCM classifier for high-dimensional data. FUZZ-IEEE 2008: 200-206 - [c35]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Keiichi Ohta:
Fuzzy c-means classifier with particle swarm optimization. FUZZ-IEEE 2008: 207-215 - [c34]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Takao Hattori:
Classifier of BOLD signals from active and inactive brain states using FCM clustering and evolutionary algorithms. FUZZ-IEEE 2008: 216-224 - [c33]Naoki Haga, Katsuhiro Honda, Hidetomo Ichihashi, Akira Notsu:
Linear fuzzy clustering of relational data based on extended Fuzzy c-Medoids. FUZZ-IEEE 2008: 366-371 - [c32]Katsuhiro Honda, Akira Notsu, Hidetomo Ichihashi:
A Perceptual Approach to User Clustering in Collaborative Filtering. GrC 2008: 281-285 - [c31]Katsuhiro Honda, Hiromichi Araki, Tomohiro Matsui, Hidetomo Ichihashi:
A new approach to robust k-Means clustering based on fuzzy principal component analysis. IJCNN 2008: 208-213 - [c30]Akira Notsu, Hidetomo Ichihashi, Katsuhiro Honda:
State and action space segmentation algorithm in Q-learning. IJCNN 2008: 2384-2389 - 2007
- [j10]Katsuhiro Honda, Hidetomo Ichihashi:
A Regularization Approach to Fuzzy Clustering with Nonlinear Membership Weights. J. Adv. Comput. Intell. Intell. Informatics 11(1): 28-34 (2007) - [j9]Chi-Hyon Oh, Katsuhiro Honda, Hidetomo Ichihashi:
Quantification of Multivariate Categorical Data Considering Typicality of Item. J. Adv. Comput. Intell. Intell. Informatics 11(1): 35-39 (2007) - [j8]Katsuhiro Honda, Ryo Uesugi, Hidetomo Ichihashi:
FCM-Type Fuzzy Clustering of Mixed Databases Considering Nominal Variable Quantification. J. Adv. Comput. Intell. Intell. Informatics 11(2): 162-167 (2007) - [j7]Katsuhiro Honda, Hidetomo Ichihashi, Francesco Masulli, Stefano Rovetta:
Linear Fuzzy Clustering With Selection of Variables Using Graded Possibilistic Approach. IEEE Trans. Fuzzy Syst. 15(5): 878-889 (2007) - [c29]Hidetomo Ichihashi, Katsuhiro Honda, Yasuhiro Kuramoto, Fumiaki Matsuura:
Fuzzy c-Means Classifier for Relational Data. CIDM 2007: 328-334 - [c28]Hidetomo Ichihashi, Katsuhiro Honda, Naho Kuwamoto, Takao Hattori:
Post-supervised Fuzzy c-Means Classifier with Hard Clustering. CIDM 2007: 583-589 - [c27]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Takafumi Yagi:
Fuzzy c-Means Classifier with Deterministic Initialization and Missing Value Imputation. FOCI 2007: 214-221 - [c26]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Takao Hattori:
Aggregation of Standard and Entropy Based Fuzzy c-Means Clustering by a Modified Objective Function. FOCI 2007: 447-453 - [c25]Katsuhiro Honda, Ryo Uesugi, Hidetomo Ichihashi, Akira Notsu:
Linear Fuzzy Clustering of Mixed Databases Based on Cluster-wise Optimal Scaling of Categorical Variables. FUZZ-IEEE 2007: 1-6 - 2006
- [j6]Katsuhiro Honda, Hidetomo Ichihashi:
Fuzzy local independent component analysis with external criteria and its application to knowledge discovery in databases. Int. J. Approx. Reason. 42(3): 159-173 (2006) - [c24]Ryo Uesugi, Katsuhiro Honda, Hidetomo Ichihashi:
Linear Fuzzy Clustering for Mixed Databases Based on Optimal Scaling. FUZZ-IEEE 2006: 778-782 - [c23]Tatsuya Maenaka, Katsuhiro Honda, Hidetomo Ichihashi:
Local Independent Component Analysis with Fuzzy Clustering and Regression-principal Component Analysis. FUZZ-IEEE 2006: 857-862 - [c22]Hidetomo Ichihashi, Katsuhiro Honda, Takao Hattori:
Regularized Discriminant in the Setting of Fuzzy c-Means Classifier. FUZZ-IEEE 2006: 875-880 - [c21]Katsuhiro Honda, Hidetomo Ichihashi, Akira Notsu:
Simultaneous Application of PLS Regression and FCM-type Clustering. FUZZ-IEEE 2006: 881-886 - [c20]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu, Takafumi Kurokawa:
Exploratory Approach to fMRI Study with Fuzzy Clustering and General Linear Model. FUZZ-IEEE 2006: 1167-1174 - [c19]Hidetomo Ichihashi, Katsuhiro Honda, Akira Notsu:
Postsupervised Hard c-Means Classifier. RSCTC 2006: 918-927 - [c18]Katsuhiro Honda, Hidetomo Ichihashi, Akira Notsu, Francesco Masulli, Stefano Rovetta:
Several Formulations for Graded Possibilistic Approach to Fuzzy Clustering. RSCTC 2006: 939-948 - [c17]Akira Notsu, Hidetomo Ichihashi, Katsuhiro Honda:
Agent-Based Simulation About Social Value Emergence Based on Perceptual Balance. SMC 2006: 724-728 - [c16]Katsuhiro Honda, Hidetomo Ichihashi, Akira Notsu:
A Sequential Learning Algorithm for Collaborative Filtering With Linear Fuzzy Clustering. SMC 2006: 1056-1061 - 2005
- [j5]Katsuhiro Honda, Hidetomo Ichihashi:
Regularized Linear Fuzzy Clustering and Probabilistic PCA Mixture Models. IEEE Trans. Fuzzy Syst. 13(4): 508-516 (2005) - [c15]Hidetomo Ichihashi, Katsuhiro Honda:
Fuzzy c-Means Classifier for Incomplete Data Sets with Outliers and Missing Values. CIMCA/IAWTIC 2005: 457-464 - [c14]Hidetomo Ichihashi, Katsuhiro Honda, Noboru Wakami:
Robust PCA with Intra-Sample Outlier Process Based on Fuzzy Mahalanobis Distances and Noise Clustering. FUZZ-IEEE 2005: 640-645 - [c13]Hidetomo Ichihashi, Katsuhiro Honda:
FCM Clustering from the View Point of Iteratively Reweighted Least Squares. FUZZ-IEEE 2005: 873-878 - [c12]Katsuhiro Honda, Hidetomo Ichihashi, Francesco Masulli, Stefano Rovetta:
Graded Possibilistic Approach to Variable Selection in Linear Fuzzy Clustering. FUZZ-IEEE 2005: 985-990 - [c11]Chi-Hyon Oh, Katsuhiro Honda, Hidetomo Ichihashi:
Quantification of Multivariate Categorical Data Considering Clusters of Items and Individuals. MDAI 2005: 164-171 - [c10]Katsuhiro Honda, Hidetomo Ichihashi:
A New Approach to Fuzzification of Memberships in Cluster Analysis. MDAI 2005: 172-182 - 2004
- [j4]Katsuhiro Honda, Hidetomo Ichihashi:
Component-wise robust linear fuzzy clustering for collaborative filtering. Int. J. Approx. Reason. 37(2): 127-144 (2004) - [j3]Katsuhiro Honda, Yoshihito Nakamura, Hidetomo Ichihashi:
Simultaneous Application of Fuzzy Clustering and Quantification with Incomplete Categorical Data. J. Adv. Comput. Intell. Intell. Informatics 8(4): 397-402 (2004) - [j2]Hidetomo Ichihashi, Katsuhiro Honda:
Application of Kernel Trick to Fuzzy c-Means with Regularization by K-L Information. J. Adv. Comput. Intell. Intell. Informatics 8(6): 566-572 (2004) - [j1]Katsuhiro Honda, Hidetomo Ichihashi:
Linear fuzzy clustering techniques with missing values and their application to local principal component analysis. IEEE Trans. Fuzzy Syst. 12(2): 183-193 (2004) - [c9]Hidetomo Ichihashi, Katsuhiro Honda, Shoichi Araki:
Fuzzy canonical correlation and cluster analysis for brain mapping on long term memory consolidated by mnemonics. FUZZ-IEEE 2004: 155-160 - [c8]Hidetomo Ichihashi, Katsuhiro Honda:
On parameter setting in applying Dave's noise fuzzy clustering to Gaussian mixture models. FUZZ-IEEE 2004: 1501-1506 - [c7]Katsuhiro Honda, Hidetomo Ichihashi:
Detection of local linear structure from data with uncertainties. FUZZ-IEEE 2004: 1507-1511 - 2002
- [c6]Hidetomo Ichihashi, Katsuhiro Honda:
Robust Clustering in Fuzzy C-Means with Regularization by Cross Entropy. FSKD 2002: 471-475 - [c5]Katsuhiro Honda, Nobuhiro Togo, Taro Fujii, Hidetomo Ichihashi:
Linear fuzzy clustering based on least absolute deviations. FUZZ-IEEE 2002: 1444-1449 - 2001
- [c4]Hidetomo Ichihashi, Kiyotaka Miyagishi, Katsuhiro Honda:
Fuzzy C-Means Clustering With Regularization by K-L Information. FUZZ-IEEE 2001: 924-927 - [c3]Katsuhiro Honda, Nobukazu Sugiura, Hidetomo Ichihashi, Shoichi Araki:
Collaborative Filtering Using Principal Component Analysis and Fuzzy Clustering. Web Intelligence 2001: 394-402 - 2000
- [c2]Chi-Hyon Oh, Eriko Ikeda, Katsuhiro Honda, Hidetomo Ichihashi:
Parameter Specification for Fuzzy Clustering by Q-Learning. IJCNN (4) 2000: 9-12 - [c1]Chi-Hyon Oh, Hirokazu Komatsu, Katsuhiro Honda, Hidetomo Ichihashi:
Fuzzy Clustering Algorithm Extracting Principal Components Independent of Subsidiary Variables. IJCNN (3) 2000: 377-380
Coauthor Index
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