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Hideyuki Imai
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2020 – today
- 2022
- [j26]Akira Tanaka, Masanari Nakamura, Hideyuki Imai:
Kernel-Based Regressors Equivalent to Stochastic Affine Estimators. IEICE Trans. Inf. Syst. 105-D(1): 116-122 (2022) - [j25]Mariko Tai, Mineichi Kudo, Akira Tanaka, Hideyuki Imai, Keigo Kimura:
Kernelized Supervised Laplacian Eigenmap for Visualization and Classification of Multi-Label Data. Pattern Recognit. 123: 108399 (2022) - 2021
- [c32]Akira Tanaka, Masanari Nakamura, Hideyuki Imai:
Model Selection of Kernel Ridge Regression for Extrapolation. MLSP 2021: 1-6 - 2020
- [j24]Hideyuki Imai:
Shift Invariance Property of a Non-Negative Matrix Factorization. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 103-A(2): 580-581 (2020) - [j23]Unhawa Ninrutsirikun, Hideyuki Imai, Bunthit Watanapa, Chonlameth Arpnikanondt:
Principal Component Clustered Factors for Determining Study Performance in Computer Programming Class. Wirel. Pers. Commun. 115(4): 2897-2916 (2020) - [c31]Akira Tanaka, Hideyuki Imai:
Kernel Ridge Regression with Autocorrelation Prior: Optimal Model and Cross-Validation. ICASSP 2020: 3872-3876
2010 – 2019
- 2019
- [j22]Akira Tanaka, Hideyuki Imai:
A Fast Cross-Validation Algorithm for Kernel Ridge Regression by Eigenvalue Decomposition. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 102-A(9): 1317-1320 (2019) - [c30]Ruoni Zhang, Hideyuki Imai, Yoshihiro Hirose:
Affine Transformation based Nonnegative Matrix Factorization. iFUZZY 2019: 343-346 - 2017
- [j21]Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto:
An Online Self-Constructive Normalized Gaussian Network with Localized Forgetting. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 100-A(3): 865-876 (2017) - [j20]Akira Tanaka, Hideyuki Imai:
Theoretical Analyses on 2-Norm-Based Multiple Kernel Regressors. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 100-A(3): 877-887 (2017) - 2016
- [j19]Sadamori Koujaku, Ichigaku Takigawa, Mineichi Kudo, Hideyuki Imai:
Dense core model for cohesive subgraph discovery. Soc. Networks 44: 143-152 (2016) - [j18]Hideaki Konno, Mineichi Kudo, Hideyuki Imai, Masanori Sugimoto:
Whisper to normal speech conversion using pitch estimated from spectrum. Speech Commun. 83: 10-20 (2016) - [c29]Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto:
Reducing Redundancy with Unit Merging for Self-constructive Normalized Gaussian Networks. ICANN (1) 2016: 444-452 - [c28]Jana Backhus, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masanori Sugimoto:
Online EM for the Normalized Gaussian Network with Weight-Time-Dependent Updates. ICONIP (4) 2016: 538-546 - 2015
- [j17]Akira Tanaka, Hirofumi Takebayashi, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo:
Ensemble and Multiple Kernel Regressors: Which Is Better? IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 98-A(11): 2315-2324 (2015) - [c27]Sadamori Koujaku, Mineichi Kudo, Ichigaku Takigawa, Hideyuki Imai:
Community Change Detection in Dynamic Networks in Noisy Environment. WWW (Companion Volume) 2015: 793-798 - 2014
- [j16]Akira Tanaka, Hideyuki Imai:
Parametric Wiener Filter with Linear Constraints for Unknown Target Signals. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 97-A(1): 322-330 (2014) - [c26]Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo:
Theoretical Analyses on Ensemble and Multiple Kernel Regressors. ACML 2014 - [c25]Hideaki Konno, Rinako Sato, Hideyuki Imai, Mineichi Kudo:
Deterioration of intelligibility in whispered Japanese speech. APSIPA 2014: 1-4 - [c24]Akira Tanaka, Hideyuki Imai:
Music-based DOA estimation by oblique projection along the signal subspace. SSP 2014: 300-303 - [c23]Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo:
Analyses on Generalization Error of Ensemble Kernel Regressors. S+SSPR 2014: 273-281 - 2012
- [c22]Katsuya Kohno, Akira Tanaka, Hideyuki Imai:
A novel criterion for quality improvement of JPEG images based on image database and re-application of JPEG. APSIPA 2012: 1-4 - [c21]Akira Tanaka, Hideyuki Imai, Koji Takamiya:
Variance analyses for kernel regressors with nested reproducing kernel hilbert spaces. ICASSP 2012: 2001-2004 - [c20]Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo:
Extended Analyses for an Optimal Kernel in a Class of Kernels with an Invariant Metric. SSPR/SPR 2012: 345-353 - 2011
- [j15]Kozo Yamada, Hirohito Sakurai, Hideyuki Imai, Yoshiharu Sato:
Robustness of resampling-based error rate estimators in two class discrimination under non-normal population. Int. J. Reason. based Intell. Syst. 3(1): 14-27 (2011) - [j14]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
A Fuzzy Weights Representation for Inner Dependence AHP. J. Adv. Comput. Intell. Intell. Informatics 15(3): 329-335 (2011) - [c19]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
A fuzzy representation for non-additive weights of AHP. FUZZ-IEEE 2011: 672-675 - [c18]Hideyuki Imai, Noriko Hara, Toshiki Yamaoka:
Observation Research of Consumer Behavior for Marketing Decision Support. HCI (23) 2011: 405-409 - [c17]Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
Theoretical analyses on a class of nested RKHS's. ICASSP 2011: 2072-2075 - 2010
- [j13]Jun Toyama, Mineichi Kudo, Hideyuki Imai:
Probably correct k-nearest neighbor search in high dimensions. Pattern Recognit. 43(4): 1361-1372 (2010) - [j12]Akira Tanaka, Hideyuki Imai, Masaaki Miyakoshi:
Kernel-induced sampling theorem. IEEE Trans. Signal Process. 58(7): 3569-3577 (2010) - [c16]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
A kind of fuzzy weights representation for inner dependence AHP. FUZZ-IEEE 2010: 1-5 - [c15]Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
A Relationship Between Generalization Error and Training Samples in Kernel Regressors. ICPR 2010: 1421-1424 - [c14]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
On a Fuzzy Weights Representation for Inner Dependence AHP. IPMU (2) 2010: 289-297
2000 – 2009
- 2009
- [c13]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
A Fuzzy Weight Representation for Inner Dependence Method AHP. IFSA/EUSFLAT Conf. 2009: 1612-1617 - [c12]Mineichi Kudo, Jun Toyama, Hideyuki Imai:
A Fast Nearest Neighbor Method Using Empirical Marginal Distribution. KES (2) 2009: 333-339 - [c11]Kozo Yamada, Hirohito Sakurai, Hideyuki Imai, Yoshiharu Sato:
Effects of Kurtosis for the Error Rate Estimators Using Resampling Methods in Two Class Discrimination. KES (2) 2009: 340-347 - 2008
- [c10]Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
Optimal Kernel in a Class of Kernels with an Invariant Metric. SSPR/SPR 2008: 530-539 - 2007
- [j11]Akira Tanaka, Hideyuki Imai, Masaaki Miyakoshi:
A Unified Framework of Subspace Identification for D.O.A. Estimation. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 90-A(2): 419-428 (2007) - [j10]Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
Integrated kernels and their properties. Pattern Recognit. 40(11): 2930-2938 (2007) - [c9]Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai:
A Fuzzy Representation for Weights of Alternatives in AHP. EUSFLAT Conf. (2) 2007: 311-316 - 2006
- [c8]Akira Tanaka, Hideyuki Imai, Masaaki Miyakoshi:
Theoretical Foundations of Second-Order-Statistics-Based Blind Source Separation for Non-Stationary Sources. ICASSP (3) 2006: 600-603 - [c7]O. Ishibashi, M. Iriguchi, Keigo Kimura, J. Ishii, D. Sasaki, Hideyuki Imai, H. Tsuchi, Hiroshi Hayama:
Panel-Sized TFT-LCD Column Driver. ISSCC 2006: 619-626 - [c6]Akira Tanaka, Masashi Sugiyama, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
Model Selection Using a Class of Kernels with an Invariant Metric. SSPR/SPR 2006: 862-870 - 2004
- [c5]Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi:
Projection Learning Based Kernel Machine Design Using Series of Monotone Increasing Reproducing Kernel Hilbert Spaces. KES 2004: 1058-1064 - [c4]Hideyuki Imai, Daigo Izawa, Kiyotaka Yoshida, Yoshiharu Sato:
On Detecting Interactions in Hayashi's Second Method of Quantification. MDAI 2004: 205-214 - [c3]Mineichi Kudo, Hideyuki Imai, Akira Tanaka, Tetsuya Murai:
A Nearest Neighbor Method Using Bisectors. SSPR/SPR 2004: 885-893 - 2003
- [j9]Ronald Waweru Mwangi, Hideyuki Imai, Yoshiharu Sato:
Multidimensional Global Optimization Using Interval Slopes. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 86-A(11): 2836-2843 (2003) - [c2]Hideyuki Imai, Vicenç Torra:
On a modeling of decision making with a twofold integral. EUSFLAT Conf. 2003: 714-717 - 2002
- [j8]Akira Tanaka, Hideyuki Imai, Masaaki Miyakoshi:
Choosing the Parameter of Image Restoration Filters by Modified Subspace Information Criterion. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 85-A(5): 1104-1110 (2002) - [j7]Hideyuki Imai, Yuying Yuan, Yoshiharu Sato:
Parameter Estimation and Image Restoration Using the Families of Projection Filters and Parametric Projection Filters. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 85-A(8): 1966-1969 (2002) - [j6]Hideyuki Imai, Masaaki Miyakoshi, Yoshiharu Sato:
Properties of the solution set of a fuzzy relation equation from the viewpoint of attainability. Soft Comput. 6(2): 87-91 (2002) - 2000
- [j5]Hideyuki Imai, Yuichiro Okahara, Masaaki Miyakoshi:
The period of powers of a fuzzy matrix. Fuzzy Sets Syst. 109(3): 405-408 (2000) - [c1]Mineichi Kudo, Hideyuki Imai, Masaru Shimbo:
A Histogram-Based Classifier on Overlapped Bins. ICPR 2000: 2029-2033
1990 – 1999
- 1998
- [j4]Hideyuki Imai, Ken Kikuchi, Masaaki Miyakoshi:
Unattainable solutions of a fuzzy relation equation. Fuzzy Sets Syst. 99(2): 193-196 (1998) - [j3]Hideyuki Imai, Akira Tanaka, Masaaki Miyakoshi:
A method of identifying influential data in fuzzy clustering. IEEE Trans. Fuzzy Syst. 6(1): 90-101 (1998) - 1997
- [j2]Hideyuki Imai, Masaaki Miyakoshi, Tsutomu Da-te:
Some properties of minimal solutions for a fuzzy relation equation. Fuzzy Sets Syst. 90(3): 335-340 (1997) - [j1]Hideyuki Imai, Akira Tanaka, Masaaki Miyakoshi:
Evaluation of optimum image restoration filters by perturbation of a degradationoperator. Syst. Comput. Jpn. 28(8-9): 25-32 (1997)
Coauthor Index
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