Norikazu Takahashi

Publication Activity (10 Years)

Years Active: 1990-2024
Publications (10 Years): 27

Top Topics

Global Convergence

Uncalibrated Photometric Stereo

Alternating Least Squares

Top Venues

Comput. Optim. Appl.

Discret. Appl. Math.

Publications

Han Xiao, Tsuyoshi Migita, Norikazu Takahashi
A New Boolean Matrix Factorization Algorithm Based on Cardano's Method. ICICT (2024)
Daiki Hirata, Norikazu Takahashi
Ensemble Learning in CNN Augmented with Fully Connected Subnetworks. IEICE Trans. Inf. Syst. 106 (7) (2023)
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 (2023)
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)
Tsuyoshi Migita, Ayane Okada, Norikazu Takahashi
Uncalibrated Photometric Stereo Using Superquadrics with Texture Estimation. IW-FCV (2022)
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) (2022)
Takumi Nasu, Tsuyoshi Migita, Norikazu Takahashi
Uncalibrated Photometric Stereo Using Superquadrics with Cast Shadow. IW-FCV (2021)
Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi
An Algorithm for Randomized Nonnegative Matrix Factorization and Its Global Convergence. SSCI (2021)
Zhuo Wu, Tsuyoshi Migita, Norikazu Takahashi
Element-Wise Alternating Least Squares Algorithm for Nonnegative Matrix Factorization on One-Hot Encoded Data. ICONIP (5) (2020)
Reiji Hayashi, Tsuyoshi Migita, Norikazu Takahashi
A Genetic Algorithm for Finding Regular Graphs with Minimum Average Shortest Path Length. SSCI (2020)
Takumi Nasu, Tsuyoshi Migita, Takeshi Shakunaga, Norikazu Takahashi
Uncalibrated Photometric Stereo Using Quadric Surfaces with Two Cameras. IW-FCV (2020)
Daiki Hirata, Norikazu Takahashi
Ensemble learning in CNN augmented with fully connected subnetworks. CoRR (2020)
Norikazu Takahashi, Daiki Hirata, Shuji Jimbo, Hiroaki Yamamoto
Band-restricted diagonally dominant matrices: Computational complexity and application. J. Comput. Syst. Sci. 101 (2019)
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)
Yohei Domen, Tsuyoshi Migita, Norikazu Takahashi
A Distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization. SSCI (2019)
Katsuki Shimada, Tsuyoshi Migita, Norikazu Takahashi
An Infinity Norm-Based Pseudo-Decentralized Discrete-Time Algorithm for Computing Algebraic Connectivity. SSCI (2019)
Takehiro Sano, Tsuyoshi Migita, Norikazu Takahashi
A Damped Newton Algorithm for Nonnegative Matrix Factorization Based on Alpha-Divergence. ICSAI (2019)
Yoshito Usuzaka, Norikazu Takahashi
A Novel NMF Algorithm for Detecting Clusters in Directed Networks. ICNC (2019)
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) (2018)
Yoshiki Satotani, Norikazu Takahashi
Depth-First Search Algorithms for Finding a Generalized Moore Graph. TENCON (2018)
Norikazu Takahashi, Kosuke Kawashima
A Simple Sufficient Condition for Convergence of Projected Consensus Algorithm. IEEE Control. Syst. Lett. 2 (3) (2018)
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) (2017)
Satoshi Nakatsu, Norikazu Takahashi
A Novel Newton-Type Algorithm for Nonnegative Matrix Factorization with Alpha-Divergence. ICONIP (1) (2017)
Takumi Kimura, Norikazu Takahashi
Gauss-Seidel HALS Algorithm for Nonnegative Matrix Factorization with Sparseness and Smoothness Constraints. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (12) (2017)
Tatsuya Fukami, Norikazu Takahashi
Graphs that locally maximize clustering coefficient in the space of graphs with a fixed degree sequence. Discret. Appl. Math. 217 (2017)
Kento Endo, Norikazu Takahashi
A new decentralized discrete-time algorithm for estimating algebraic connectivity of multiagent networks. APCCAS (2016)
Norikazu Takahashi, Masato Seki
Multiplicative update for a class of constrained optimization problems related to NMF and its global convergence. EUSIPCO (2016)
Takumi Kimura, Norikazu Takahashi
Global convergence of a modified HALS algorithm for nonnegative matrix factorization. CAMSAP (2015)
Norikazu Takahashi, Ryota Hibi
Global convergence of modified multiplicative updates for nonnegative matrix factorization. Comput. Optim. Appl. 57 (2) (2014)
Tatsuya Fukami, Norikazu Takahashi
New classes of clustering coefficient locally maximizing graphs. Discret. Appl. Math. 162 (2014)
Jiro Katayama, Norikazu Takahashi, Jun'ichi Takeuchi
Boundedness of modified multiplicative updates for nonnegative matrix factorization. CAMSAP (2013)
Kotaro Yamaguchi, Masanori Kawakita, Norikazu Takahashi, Jun'ichi Takeuchi
Information Theoretic Limit of Single-Frame Super-Resolution. EST (2012)
Ryota Hibi, Norikazu Takahashi
A Modified Multiplicative Update Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization and Its Global Convergence. ICONIP (2) (2011)
Norikazu Takahashi
On clustering coefficients of graphs with the fixed numbers of vertices and edges. ECCTD (2009)
Jun Guo, Norikazu Takahashi
Global Convergence Analysis of Decomposition Methods for Support Vector Regression. ISNN (1) (2008)
Norikazu Takahashi, Jun Guo, Tetsuo Nishi
Global Convergence of SMO Algorithm for Support Vector Regression. IEEE Trans. Neural Networks 19 (6) (2008)
Norikazu Takahashi, Yasuhiro Minetoma
On asymptotic behavior of state trajectories of piecewise-linear recurrent neural networks generating periodic sequence of binary vectors. IJCNN (2008)
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. (11) (2008)
Norikazu Takahashi, Ken Ishitobi, Tetsuo Nishi
Sufficient Conditions for 1-D CNNs with Opposite-Sign Templates to Perform Connected Component Detection. ISCAS (2007)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
An Efficient Method for Simplifying Decision Functions of Support Vector Machines. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (10) (2006)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
A Novel Sequential Minimal Optimization Algorithm for Support Vector Regression. ICONIP (1) (2006)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
Convergence Proof of a Sequential Minimal Optimization Algorithm for Support Vector Regression. IJCNN (2006)
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. (10) (2006)
Norikazu Takahashi, Tetsuo Nishi
A sufficient condition for 1D CNNs with antisymmetric templates to perform connected component detection. ISCAS (2006)
Norikazu Takahashi, Tetsuo Nishi
Global Convergence of Decomposition Learning Methods for Support Vector Machines. IEEE Trans. Neural Networks 17 (6) (2006)
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 (8) (2006)
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. (12) (2006)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
A learning algorithm for improving the classification speed of support vector machines. ECCTD (2005)
Norikazu Takahashi, Tetsuo Nishi
On complete stability of three-cell CNNs with opposite-sign templates. ISCAS (5) (2005)
Norikazu Takahashi, Tetsuo Nishi
Rigorous proof of termination of SMO algorithm for support vector Machines. IEEE Trans. Neural Networks 16 (3) (2005)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
A learning algorithm for enhancing the generalization ability of support vector machines. ISCAS (4) (2005)
Norikazu Takahashi, Tsuyoshi Yamakawa, Tetsuo Nishi
Realization of limit cycles by neural networks with piecewise linear activation function. ECCTD (2005)
Jun Guo, Norikazu Takahashi, Tetsuo Nishi
A Learning Method for Robust Support Vector Machines. ISNN (1) (2004)
Norikazu Takahashi, Tetsuo Nishi
Global convergence analysis of decomposition methods for support vector machines. ISCAS (5) (2004)
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. (9) (2003)
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)
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. (9) (2002)
Norikazu Takahashi, Tetsuo Nishi
A Generalization of Some Complete Stability Conditions for Cellular Neural Networks with Delay. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (9) (2002)
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)