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ORCIDYoshifumi Kusunoki
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2020 – today
- 2024
[c25]Kensuke Ajimoto, Yuma Yamamoto, Yoshifumi Kusunoki, Tomoharu Nakashima:
A Study on Multi-Class Online Fuzzy Classifiers for Dynamic Environments. FUZZ 2024: 1-7- [c24]Yoshifumi Kusunoki
:
Revised Margin-Maximization Method for Fuzzy Nearest Prototype Classification. MDAI 2024: 140-151 - 2023
- [c23]Yoshifumi Kusunoki:
Maximum-Margin Nearest Prototype Classifiers with the Sum-over-Others Loss Function and a Performance Evaluation. IUKM (2) 2023: 37-46 - 2022
- [j7]Keiji Tatsumi, Shunsuke Tsujioka, Ryota Masui, Yoshifumi Kusunoki, Yeboon Yun:
Determination of reinforcement degrees in constructing large-scale structures by using multiclass support vector machines. Knowl. Based Syst. 249: 108807 (2022) - [c22]Yoshifumi Kusunoki, Katsuhiko Kojima, Keiji Tatsumi:
Transductive Learning Based on Low-Rank Representation with Convex Constraints. IUKM 2022: 291-301 - 2021
- [j6]Yoshifumi Kusunoki, Jerzy Blaszczynski, Masahiro Inuiguchi, Roman Slowinski:
Empirical risk minimization for dominance-based rough set approaches. Inf. Sci. 567: 395-417 (2021) - [c21]Tatsuhisa Watanabe, Tomoharu Nakashima, Yoshifumi Kusunoki:
Change Detection For Area Surveillance Using A Moving Camera. ECMS 2021: 220-226 - [c20]Yasuhiro Matsuda, Tomoharu Nakashima, Yoshifumi Kusunoki:
Employing a View Field in Autonomous Robots and Optimization of Checkpoint Placement in Area Surveillance. SICE 2021: 27-32 - [c19]Keiji Tatsumi, Ryota Masui, Shunsuke Tsujioka, Yoshifumi Kusunoki, Yeboon Yun:
Multiclass Support Vector Machines for Determination of Reinforcement Degree in Constructing Large-scale Structures Based on Data Characteristics. SMC 2021: 1513-1518 - 2020
- [c18]Katsuhiko Kojima, Yoshifumi Kusunoki, Keiji Tatsumi:
Manifold Learning with Intrinsic Distance Estimation Using Kernelized Linear Model for Metric Tensors. SMC 2020: 3558-3563
2010 – 2019
- 2019
- [c17]Yoshifumi Kusunoki, Keiji Tatsumi:
Scalarization for Approximate Multiobjective Multiclass Support Vector Machine Using the Large-k Norm. EUSFLAT Conf. 2019 - [c16]Yoshifumi Kusunoki, Jerzy Blaszczynski, Masahiro Inuiguchi, Roman Slowinski:
Interpretation of Variable Consistency Dominance-Based Rough Set Approach by Minimization of Asymmetric Loss Function. IUKM 2019: 135-145 - [c15]Keiji Tatsumi, Takahumi Sugimoto, Yoshifumi Kusunoki:
Approximate Multiobjective Multiclass Support Vector Machine Restricting Classifier Candidates Based on k-Means Clustering. IUKM 2019: 271-283 - 2018
- [j5]Yoshifumi Kusunoki, Chiharu Wakou, Keiji Tatsumi:
Maximum-Margin Model for Nearest Prototype Classifiers. J. Adv. Comput. Intell. Intell. Informatics 22(4): 565-577 (2018) - [c14]Yoshifumi Kusunoki, Keiji Tatsumi:
A Multi-class Support Vector Machine Based on Geometric Margin Maximization. IUKM 2018: 101-113 - [c13]Masaki Saito, Yoshifumi Kusunoki:
Axiomatization and Generalization of the Core for Assignment Games on the Complete Graph. SMC 2018: 1593-1598 - [c12]Yasuhiro Matsugi, Takafumi Sugimoto, Yuxiao Qi, Yoshifumi Kusunoki, Keiji Tatsumi:
Approximate Multiobjective Multiclass SVM by Using the Reference Point Method. SMC 2018: 3535-3540 - 2017
- [j4]Yoshifumi Kusunoki, Tetsuzo Tanino:
Investigation on irreducible cost vectors in minimum cost arborescence problems. Eur. J. Oper. Res. 261(1): 214-221 (2017) - [c11]Chiharu Wakou, Yoshifumi Kusunoki, Keiji Tatsumi:
Learning prototype-based classifiers by margin maximization. IFSA-SCIS 2017: 1-6 - 2015
- [c10]Jerzy Blaszczynski, Yoshifumi Kusunoki, Masahiro Inuiguchi, Roman Slowinski:
Empirical Risk Minimization for Variable Consistency Dominance-Based Rough Set Approach. RSFDGrC 2015: 63-72 - [p1]Yoshifumi Kusunoki, Masahiro Inuiguchi:
Structure-Based Attribute Reduction: A Rough Set Approach. Feature Selection for Data and Pattern Recognition 2015: 113-160 - 2014
- [c9]Yoshifumi Kusunoki, Tetsuzo Tanino:
Boolean kernels and clustering with pairwise constraints. GrC 2014: 141-146 - 2013
- [c8]Yoshifumi Kusunoki, Tetsuzo Tanino:
Specific-to-general approach for rule induction using discernibility based dissimilarity. GrC 2013: 178-181 - [c7]Yoshifumi Kusunoki, Jerzy Blaszczynski, Masahiro Inuiguchi, Roman Slowinski:
Empirical Risk Minimization for Variable Precision Dominance-Based Rough Set Approach. RSKT 2013: 133-144 - 2011
- [j3]Yoshifumi Kusunoki, Masahiro Inuiguchi:
Variable Precision Rough Set Model in Information Tables with Missing Values. J. Adv. Comput. Intell. Intell. Informatics 15(1): 110-116 (2011) - [c6]Yoshifumi Kusunoki, Tetsuzo Tanino:
Agglomerative hierarchical clustering with dissimilarity using discernibility on attribute subsets for nominal data sets. GrC 2011: 357-362 - [c5]Masahiro Inuiguchi, Masahiko Tsuji, Yoshifumi Kusunoki, Masayo Tsurumi:
LEM2-Based Rule Induction from Data Tables with Imprecise Evaluations. RSKT 2011: 201-207 - 2010
- [j2]Yoshifumi Kusunoki, Masahiro Inuiguchi:
A unified approach to reducts in dominance-based rough set approach. Soft Comput. 14(5): 507-515 (2010) - [c4]Yoshifumi Kusunoki, Masahiro Inuiguchi, Masanori Inoue, Tetsuzo Tanino:
Rule Induction from Information Tables with Ordinal Decision Attributes. GrC 2010: 271-276 - [c3]Masahiro Inuiguchi, Ryuta Enomoto, Yoshifumi Kusunoki:
Non-hierarchical Clustering of Decision Tables toward Rough Set-Based Group Decision Aid. MDAI 2010: 195-206
2000 – 2009
- 2009
- [j1]Masahiro Inuiguchi, Yukihiro Yoshioka, Yoshifumi Kusunoki:
Variable-precision dominance-based rough set approach and attribute reduction. Int. J. Approx. Reason. 50(8): 1199-1214 (2009) - 2008
- [c2]Yoshifumi Kusunoki, Masahiro Inuiguchi:
A Comprehensive Study on Reducts in Dominance-Based Rough Set Approach. MDAI 2008: 167-178 - 2006
- [c1]Yoshifumi Kusunoki, Masahiro Inuiguchi:
Rule Induction Via Clustering Decision Classes. RSCTC 2006: 928-938
Coauthor Index
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