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Norikazu Takahashi
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2020 – today
- 2024
- [c35]Han Xiao, Tsuyoshi Migita, Norikazu Takahashi:
A New Boolean Matrix Factorization Algorithm Based on Cardano's Method. ICICT 2024: 51-56 - 2023
- [j23]Daiki Hirata, Norikazu Takahashi:
Ensemble Learning in CNN Augmented with Fully Connected Subnetworks. IEICE Trans. Inf. Syst. 106(7): 1258-1261 (2023) - [j22]Norikazu Takahashi, Tsuyoshi Yamakawa, Yasuhiro Minetoma, Tetsuo Nishi, Tsuyoshi Migita:
Design of continuous-time recurrent neural networks with piecewise-linear activation function for generation of prescribed sequences of bipolar vectors. Neural Networks 164: 588-605 (2023) - 2022
- [j21]Yoshiki Satotani, Tsuyoshi Migita, Norikazu Takahashi:
An algorithm for updating betweenness centrality scores of all vertices in a graph upon deletion of a single edge. J. Complex Networks 10(4) (2022) - [j20]Takehiro Sano, Tsuyoshi Migita, Norikazu Takahashi:
A novel update rule of HALS algorithm for nonnegative matrix factorization and Zangwill's global convergence. J. Glob. Optim. 84(3): 755-781 (2022) - [c34]Tsuyoshi Migita, Ayane Okada, Norikazu Takahashi:
Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation. IW-FCV 2022: 34-48 - 2021
- [c33]Takumi Nasu, Tsuyoshi Migita, Norikazu Takahashi:
Uncalibrated Photometric Stereo Using Superquadrics with Cast Shadow. IW-FCV 2021: 267-280 - [c32]Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi:
An Algorithm for Randomized Nonnegative Matrix Factorization and Its Global Convergence. SSCI 2021: 1-7 - 2020
- [c31]Takumi Nasu, Tsuyoshi Migita, Takeshi Shakunaga, Norikazu Takahashi:
Uncalibrated Photometric Stereo Using Quadric Surfaces with Two Cameras. IW-FCV 2020: 318-332 - [c30]Zhuo Wu, Tsuyoshi Migita, Norikazu Takahashi:
Element-Wise Alternating Least Squares Algorithm for Nonnegative Matrix Factorization on One-Hot Encoded Data. ICONIP (5) 2020: 342-350 - [c29]Reiji Hayashi, Tsuyoshi Migita, Norikazu Takahashi:
A Genetic Algorithm for Finding Regular Graphs with Minimum Average Shortest Path Length. SSCI 2020: 2431-2436 - [i1]Daiki Hirata, Norikazu Takahashi:
Ensemble learning in CNN augmented with fully connected subnetworks. CoRR abs/2003.08562 (2020)
2010 – 2019
- 2019
- [j19]Norikazu Takahashi, Daiki Hirata, Shuji Jimbo, Hiroaki Yamamoto:
Band-restricted diagonally dominant matrices: Computational complexity and application. J. Comput. Syst. Sci. 101: 100-111 (2019) - [c28]Yuki Taketa, Yuta Kodera, Shogo Tanida, Takuya Kusaka, Yasuyuki Nogami, Norikazu Takahashi, Satoshi Uehara:
Mutual Relationship between the Neural Network Model and Linear Complexity for Pseudorandom Binary Number Sequence. CANDAR Workshops 2019: 394-400 - [c27]Yoshito Usuzaka, Norikazu Takahashi:
A Novel NMF Algorithm for Detecting Clusters in Directed Networks. ICNC 2019: 148-152 - [c26]Takehiro Sano, Tsuyoshi Migita, Norikazu Takahashi:
A Damped Newton Algorithm for Nonnegative Matrix Factorization Based on Alpha-Divergence. ICSAI 2019: 463-468 - [c25]Katsuki Shimada, Tsuyoshi Migita, Norikazu Takahashi:
An Infinity Norm-Based Pseudo-Decentralized Discrete-Time Algorithm for Computing Algebraic Connectivity. SSCI 2019: 1292-1298 - [c24]Yohei Domen, Tsuyoshi Migita, Norikazu Takahashi:
A Distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization. SSCI 2019: 1332-1337 - 2018
- [j18]Norikazu Takahashi, Jiro Katayama, Masato Seki, Jun'ichi Takeuchi:
A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization. Comput. Optim. Appl. 71(1): 221-250 (2018) - [j17]Norikazu Takahashi, Kosuke Kawashima:
A Simple Sufficient Condition for Convergence of Projected Consensus Algorithm. IEEE Control. Syst. Lett. 2(3): 537-542 (2018) - [c23]Yoshiki Satotani, Norikazu Takahashi:
Depth-First Search Algorithms for Finding a Generalized Moore Graph. TENCON 2018: 832-837 - 2017
- [j16]Tatsuya Fukami, Norikazu Takahashi:
Graphs that locally maximize clustering coefficient in the space of graphs with a fixed degree sequence. Discret. Appl. Math. 217: 525-535 (2017) - [j15]Takumi Kimura, Norikazu Takahashi:
Gauss-Seidel HALS Algorithm for Nonnegative Matrix Factorization with Sparseness and Smoothness Constraints. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 100-A(12): 2925-2935 (2017) - [j14]Kohnosuke Ogiwara, Tatsuya Fukami, Norikazu Takahashi:
Maximizing Algebraic Connectivity in the Space of Graphs With a Fixed Number of Vertices and Edges. IEEE Trans. Control. Netw. Syst. 4(2): 359-368 (2017) - [c22]Satoshi Nakatsu, Norikazu Takahashi:
A Novel Newton-Type Algorithm for Nonnegative Matrix Factorization with Alpha-Divergence. ICONIP (1) 2017: 335-344 - 2016
- [c21]Kento Endo, Norikazu Takahashi:
A new decentralized discrete-time algorithm for estimating algebraic connectivity of multiagent networks. APCCAS 2016: 232-235 - [c20]Norikazu Takahashi, Masato Seki:
Multiplicative update for a class of constrained optimization problems related to NMF and its global convergence. EUSIPCO 2016: 438-442 - 2015
- [c19]Takumi Kimura, Norikazu Takahashi:
Global convergence of a modified HALS algorithm for nonnegative matrix factorization. CAMSAP 2015: 21-24 - 2014
- [j13]Norikazu Takahashi, Ryota Hibi:
Global convergence of modified multiplicative updates for nonnegative matrix factorization. Comput. Optim. Appl. 57(2): 417-440 (2014) - [j12]Tatsuya Fukami, Norikazu Takahashi:
New classes of clustering coefficient locally maximizing graphs. Discret. Appl. Math. 162: 202-213 (2014) - 2013
- [c18]Jiro Katayama, Norikazu Takahashi, Jun'ichi Takeuchi:
Boundedness of modified multiplicative updates for nonnegative matrix factorization. CAMSAP 2013: 252-255 - 2012
- [c17]Kotaro Yamaguchi, Masanori Kawakita, Norikazu Takahashi, Jun'ichi Takeuchi:
Information Theoretic Limit of Single-Frame Super-Resolution. EST 2012: 82-85 - 2011
- [c16]Ryota Hibi, Norikazu Takahashi:
A Modified Multiplicative Update Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization and Its Global Convergence. ICONIP (2) 2011: 655-662
2000 – 2009
- 2009
- [c15]Norikazu Takahashi:
On clustering coefficients of graphs with the fixed numbers of vertices and edges. ECCTD 2009: 814-817 - 2008
- [j11]Norikazu Takahashi, Makoto Nagayoshi, Susumu Kawabata, Tetsuo Nishi:
Stable Patterns Realized by a Class of One-Dimensional Two-Layer CNNs. IEEE Trans. Circuits Syst. I Regul. Pap. 55-I(11): 3607-3620 (2008) - [j10]Norikazu Takahashi, Jun Guo, Tetsuo Nishi:
Global Convergence of SMO Algorithm for Support Vector Regression. IEEE Trans. Neural Networks 19(6): 971-982 (2008) - [c14]Norikazu Takahashi, Yasuhiro Minetoma:
On asymptotic behavior of state trajectories of piecewise-linear recurrent neural networks generating periodic sequence of binary vectors. IJCNN 2008: 484-489 - [c13]Jun Guo, Norikazu Takahashi:
Global Convergence Analysis of Decomposition Methods for Support Vector Regression. ISNN (1) 2008: 663-673 - 2007
- [c12]Norikazu Takahashi, Ken Ishitobi, Tetsuo Nishi:
Sufficient Conditions for 1-D CNNs with Opposite-Sign Templates to Perform Connected Component Detection. ISCAS 2007: 3159-3162 - 2006
- [j9]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
An Efficient Method for Simplifying Decision Functions of Support Vector Machines. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 89-A(10): 2795-2802 (2006) - [j8]Tetsuo Nishi, Hajime Hara, Norikazu Takahashi:
Necessary and Sufficient Conditions for a 1-D DBCNN with an Input to Be Stable in terms of Connection Coefficients. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 89-A(10): 2825-2832 (2006) - [j7]Tetsuo Nishi, Norikazu Takahashi, Hajime Hara:
Necessary and Sufficient Conditions for One-Dimensional Discrete-Time Autonomous Binary Cellular Neural Networks to Be Stable. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 89-A(12): 3693-3698 (2006) - [j6]Norikazu Takahashi, Tetsuo Nishi:
Necessary and Sufficient Condition for a Class of Planar Dynamical Systems Related to CNNs to be Completely Stable. IEEE Trans. Circuits Syst. II Express Briefs 53-II(8): 727-733 (2006) - [j5]Norikazu Takahashi, Tetsuo Nishi:
Global Convergence of Decomposition Learning Methods for Support Vector Machines. IEEE Trans. Neural Networks 17(6): 1362-1369 (2006) - [c11]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
A Novel Sequential Minimal Optimization Algorithm for Support Vector Regression. ICONIP (1) 2006: 827-836 - [c10]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
Convergence Proof of a Sequential Minimal Optimization Algorithm for Support Vector Regression. IJCNN 2006: 355-362 - [c9]Norikazu Takahashi, Tetsuo Nishi:
A sufficient condition for 1D CNNs with antisymmetric templates to perform connected component detection. ISCAS 2006 - 2005
- [j4]Norikazu Takahashi, Tetsuo Nishi:
Rigorous proof of termination of SMO algorithm for support vector Machines. IEEE Trans. Neural Networks 16(3): 774-776 (2005) - [c8]Norikazu Takahashi, Tsuyoshi Yamakawa, Tetsuo Nishi:
Realization of limit cycles by neural networks with piecewise linear activation function. ECCTD 2005: 7-10 - [c7]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
A learning algorithm for improving the classification speed of support vector machines. ECCTD 2005: 381-384 - [c6]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
A learning algorithm for enhancing the generalization ability of support vector machines. ISCAS (4) 2005: 3631-3634 - [c5]Norikazu Takahashi, Tetsuo Nishi:
On complete stability of three-cell CNNs with opposite-sign templates. ISCAS (5) 2005: 4673-4676 - 2004
- [c4]Norikazu Takahashi, Tetsuo Nishi:
Global convergence analysis of decomposition methods for support vector machines. ISCAS (5) 2004: 728-731 - [c3]Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
A Learning Method for Robust Support Vector Machines. ISNN (1) 2004: 474-479 - 2003
- [j3]Jun Guo, Tetsuo Nishi, Norikazu Takahashi:
A Method for Solving Optimization Problems with Equality Constraints by Using the SPICE Program. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 86-A(9): 2325-2332 (2003) - 2002
- [j2]Hidenori Sato, Tetsuo Nishi, Norikazu Takahashi:
Necessary and Sufficient Conditions for One-Dimensional Discrete-Time Binary Cellular Neural Networks with Unspecified Fixed Boundaries to Be Stable. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 85-A(9): 2036-2043 (2002) - [j1]Norikazu Takahashi, Tetsuo Nishi:
A Generalization of Some Complete Stability Conditions for Cellular Neural Networks with Delay. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 85-A(9): 2044-2051 (2002) - [c2]Tetsuo Nishi, Hidenori Sato, Norikazu Takahashi:
Necessary and sufficient conditions for one-dimensional discrete-time binary cellular neural networks with both A- and B-templates to be stable. ISCAS (1) 2002: 633-636
1990 – 1999
- 1990
- [c1]Hitomi Sato, Norikazu Takahashi, Yusuke Matsunaga, Masahiro Fujita:
Boolean technology mapping for both ECI and CMOS circuits based on permissible functions and binary decision diagrams. ICCD 1990: 286-290
Coauthor Index
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last updated on 2024-08-05 20:20 CEST by the dblp team
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