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ORCIDHiroshi Yadohisa
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2020 – today
- 2024
[j15]Masaaki Okabe
, Jun Tsuchida, Hiroshi Yadohisa:
F-measure maximizing logistic regression. Commun. Stat. Simul. Comput. 53(5): 2554-2564 (2024)- 2023
- [j14]Ippei Takasawa, Kensuke Tanioka, Hiroshi Yadohisa:
Clustered Sparse Structural Equation Modeling for Heterogeneous Data. J. Classif. 40(3): 588-613 (2023) - 2021
- [j13]Satoshi Goto, Mariko Takagishi, Hiroshi Yadohisa:
Clustering for time-varying relational count data. Comput. Stat. Data Anal. 156: 107123 (2021) - [c14]Kenta Sakamoto, Masaaki Okabe, Hiroshi Yadohisa:
Generalized canonical correlation analysis for labeled data. KES 2021: 517-525 - 2020
- [c13]Ryo Otani, Hiroshi Yadohisa:
Estimation of causal effect using propensity score and weighted-average method. KES 2020: 810-817
2010 – 2019
- 2019
- [j12]Hiroyasu Abe, Hiroshi Yadohisa:
Orthogonal nonnegative matrix tri-factorization based on Tweedie distributions. Adv. Data Anal. Classif. 13(4): 825-853 (2019) - [j11]Kensuke Tanioka, Hiroshi Yadohisa:
Simultaneous Method of Orthogonal Non-metric Non-negative Matrix Factorization and Constrained Non-hierarchical Clustering. J. Classif. 36(1): 73-93 (2019) - [i1]Masaaki Okabe, Jun Tsuchida, Hiroshi Yadohisa:
F-measure Maximizing Logistic Regression. CoRR abs/1905.02535 (2019) - 2018
- [j10]Kensuke Tanioka, Hiroshi Yadohisa:
Unfolding Models for Asymmetric Dissimilarity Data With External Information Based on Path Structures. Int. J. Softw. Innov. 6(3): 53-66 (2018) - 2017
- [j9]Hiroyasu Abe, Hiroshi Yadohisa:
A non-negative matrix factorization model based on the zero-inflated Tweedie distribution. Comput. Stat. 32(2): 475-499 (2017) - [c12]Jun Tsuchida, Hiroshi Yadohisa:
Two-Mode Three-Way Dominance Points Model for Periodic Dissimilarity. ACIT/CSII/BCD 2017: 314-319 - [c11]Kensuke Tanioka, Hiroshi Yadohisa:
Generalized Structured Component Analysis for Dissimilarity Data and Multivariate Data. ACIT/CSII/BCD 2017: 320-325 - 2016
- [c10]Jun Tsuchida, Hiroshi Yadohisa:
Connected Categorical Canonical Covariance Analysis for Three-mode Three-way data Sets Based on Tucker Model. KES 2016: 912-919 - 2015
- [j8]Masaki Mitsuhiro, Hiroshi Yadohisa:
Reduced k-means clustering with MCA in a low-dimensional space. Comput. Stat. 30(2): 463-475 (2015) - [c9]Mariko Takagishi, Hiroshi Yadohisa:
Semi-supervised Clustering for Sparsely Sampled Longitudinal Data. Complex Adaptive Systems 2015: 18-23 - 2012
- [j7]Koya Tamura, Kenji Hatano, Hiroshi Yadohisa:
A Retrieval Method Based on Language Model Considering Neighboring Contents. J. Digit. Inf. Manag. 10(1): 1-9 (2012) - [c8]Kensuke Tanioka, Hiroshi Yadohisa:
Subspace Hierarchical Clustering for Three-way Three-mode Data using Quadratic Regularization. Complex Adaptive Systems 2012: 248-253 - 2011
- [j6]Kensuke Tanioka, Hiroshi Yadohisa:
Hierarchical clustering algorithm with combined criteria for large and complex similarity data. Int. J. Knowl. Eng. Soft Data Paradigms 3(2): 121-131 (2011) - [c7]Ikufumi Takagi, Hiroshi Yadohisa:
Correspondence analysis for symbolic contingency tables based on interval algebra. Complex Adaptive Systems 2011: 352-357 - [c6]Yoshikazu Terada, Hiroshi Yadohisa:
Multidimensional scaling with the nested hypersphere model for percentile dissimilarities. Complex Adaptive Systems 2011: 364-369 - 2010
- [c5]Kensuke Tanioka, Hiroshi Yadohisa:
Effect of Data Standardization on the Result of k-Means Clustering. GfKl 2010: 59-67 - [c4]Yuichi Saito, Hiroshi Yadohisa:
Visualization of Asymmetric Clustering Result with Digraph and Dendrogram. GfKl 2010: 151-159 - [c3]Koya Tamura, Kenji Hatano, Hiroshi Yadohisa:
Characterizing Web pages based on the query likelihoods of neighboring pages. ICDIM 2010: 392-397
2000 – 2009
- 2009
- [j5]Masateru Tsunoda, Akito Monden, Hiroshi Yadohisa, Nahomi Kikuchi, Ken-ichi Matsumoto:
Software development productivity of Japanese enterprise applications. Inf. Technol. Manag. 10(4): 193-205 (2009) - 2007
- [j4]Akinobu Takeuchi, Takayuki Saito, Hiroshi Yadohisa:
Asymmetric Agglomerative Hierarchical Clustering Algorithms and Their Evaluations. J. Classif. 24(1): 123-143 (2007) - [j3]Shuichi Tokushige, Hiroshi Yadohisa, Koichi Inada:
Crisp and fuzzy k-means clustering algorithms for multivariate functional data. Comput. Stat. 22(1): 1-16 (2007) - 2006
- [c2]Masateru Tsunoda, Akito Monden, Hiroshi Yadohisa, Nahomi Kikuchi, Ken-ichi Matsumoto:
Productivity analysis of Japanese enterprise software development projects. MSR 2006: 14-17 - 2002
- [j2]Tatsuki Inoue, Yumi Asahi, Hiroshi Yadohisa, Yoshiro Yamamoto:
A Statistical Data Representation System on the Web. Comput. Stat. 17(3): 367-378 (2002) - [j1]Akinobu Takeuchi, Hiroshi Yadohisa, Kazunori Yamaguchi, Michiko Watanabe, Chooichiro Asano:
Dynamic Link Library for Statistical Analysis and Its Excel Interface. Comput. Stat. 17(3): 439-452 (2002) - [c1]Akinobu Takeuchi, Hiroshi Yadohisa, Kazunori Yamaguchi, Michiko Watanabe, Chooichiro Asano:
Statistical Computing on Web Browsers with the Dynamic Link Library. COMPSTAT 2002: 551-556
Coauthor Index
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