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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MSS, NLP (Joint) |
2020-03-09 09:50 |
Aichi | (Cancelled but technical report was issued) |
A Distributed Algorithm for Solving Sandberg-Willson Equations Based on Sequential Minimization of Convex Quadratic Functions Masaaki Takeuchi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.)  NLP2019-115 |
We propose a new distributed algorithm for multi-agent networks to solve Sandberg-Willson equations, which are well-know... [more] | NLP2019-115 pp.13-18 |
| MSS, NLP (Joint) |
2020-03-09 10:15 |
Aichi | (Cancelled but technical report was issued) |
A projected consensus-based algorithm for minimizing the maximum error of a system of linear equations with nonnegativity constraints Kosuke Kawashima, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2019-116 |
If a system of linear equations with nonnegativity constraints has a solution then it can be considered as a constrained... [more] | NLP2019-116 pp.19-23 |
| SIS | 2019-12-12 15:45 |
Okayama | Okayama University of Science | [Invited Talk]
Consensus-Based Distributed Algorithms and Applications to Machine Learning Norikazu Takahashi (Okayama Univ.) SIS2019-29 |
Recently, consensus-based distributed optimization methods for multi-agent systems have been vigorously studied in the f... [more] | SIS2019-29 p.35 |
| IT, ISEC, WBS | 2019-03-07 15:30 |
Tokyo | University of Electro-Communications | Analyzing Final Round Key of AES Implemented on Microcomputer using Neural Network Satoshi Kosugi, Sho Joichi, Ken Ikuta, Takuya Kusaka, Yasuyuki Nogami, Norikazu Takahashi (Okayama University) IT2018-86 ISEC2018-92 WBS2018-87 |
A side channel attack is an attack method that enable external key estimation by observing secondary information generat... [more] | IT2018-86 ISEC2018-92 WBS2018-87 pp.71-76 |
| NLP, NC (Joint) |
2019-01-24 15:00 |
Hokkaido | The Centennial Hall, Hokkaido Univ. | A Genetic Algorithm-Based Method for Finding Approximate Solutions to Minimum Steiner Tree Problems Li-Ping Zhang, Norikazu Takahashi (Okayama Univ.), Zong-Xiao Yang (HAUST) NLP2018-121 |
The Euclidean Steiner Tree Problem (ESTP) is a classical combinatorial optimization problem that appears in various fiel... [more] | NLP2018-121 pp.131-136 |
| NLP, NC (Joint) |
2019-01-24 15:20 |
Hokkaido | The Centennial Hall, Hokkaido Univ. | A New Method for Deriving Multiplicative Update Rules for NMF with Error Functions Containing Logarithm Akihiro Koso, Norikazu Takahashi (Okayama Univ.) NLP2018-122 |
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix X into two nonnegative... [more] | NLP2018-122 pp.137-142 |
| CAS, NLP | 2018-10-19 14:45 |
Miyagi | Tohoku Univ. | Convergence of a Pseudo-Decentralized Discrete-Time Algorithm for Computing Algebraic Connectivity
-- Analysis of the Case Where Algebraic Connectivity is Repeated -- Tomohisa Urakami, Norikazu Takahashi (Okayama Univ.) CAS2018-58 NLP2018-93 |
The algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, is ... [more] | CAS2018-58 NLP2018-93 pp.115-120 |
| NLP | 2018-08-08 14:35 |
Kagawa | Saiwai-cho Campus, Kagawa Univ. | Reconstruction of CT images by iterative Least Squares Methods with Nonnegative Constraint Hiromasa Kohno, Yuichi Tanji, Ken'ichi Fujimoto, Hiroyuki Kitajima, Yo Horikawa (Kagawa Univ.), Norikazu Takahashi (Okayama Univ.) NLP2018-57 |
[more] | NLP2018-57 pp.25-29 |
| NLP | 2018-08-09 09:30 |
Kagawa | Saiwai-cho Campus, Kagawa Univ. | Derivation and Experimental Evaluation of a Novel Nonnegative Matrix Factorization Algorithm for Discovering Communities Yoshito Usuzaka, Norikazu Takahashi (Okayama Univ.) NLP2018-64 |
Community discovery is an important technique for a better understanding of the structure of a network. We consider the ... [more] | NLP2018-64 pp.57-62 |
| NLP | 2018-08-09 09:55 |
Kagawa | Saiwai-cho Campus, Kagawa Univ. | A Convergence Condition for the Projected Consensus Algorithm on a Network with a Fixed Topology Kosuke Kawashima, Norikazu Takahashi (Okayama Univ.) NLP2018-65 |
This report studies the problem of making the states of all agents in a network converge to the same point in the inters... [more] | NLP2018-65 pp.63-68 |
| NLP, CCS | 2018-06-10 11:20 |
Kyoto | Kyoto Terrsa | Some Efficient Methods for Searching Generalized Moore Graphs Yoshiki Satotani, Norikazu Takahashi (Okayama Univ.) NLP2018-43 CCS2018-16 |
Computer networks used for high performance computing are often modeled by undirected regular graphs, and the average sh... [more] | NLP2018-43 CCS2018-16 pp.85-90 |
| NLP | 2018-04-27 14:45 |
Kumamoto | Kumaoto Univ. | A Distributed Algorithm for Multi-Agent Networks to Solve Sandberg-Willson Equations Masaaki Takeuchi, Norikazu Takahashi (Okayama Univ.) NLP2018-23 |
We propose a distributed algorithm for multi-agent networks to solve Sandberg-Willson equations, which are well-known in... [more] | NLP2018-23 pp.111-116 |
| MBE, NC, NLP (Joint) |
2018-01-26 13:00 |
Fukuoka | Kyushu Institute of Technology | Equilibrium Point Analysis of a Truly Decentralized Discrete-Time Algorithm for Algebraic Connectivity Estimation Kento Endo, Norikazu Takahashi (Okayama Univ.), Sang-Gu Lee (Sungkyunkwan Univ.) NLP2017-89 |
The second smallest eigenvalue of the Laplacian matrix of a network, also known as the algebraic connectivity, is an ind... [more] | NLP2017-89 pp.17-22 |
| MBE, NC, NLP (Joint) |
2018-01-26 13:25 |
Fukuoka | Kyushu Institute of Technology | Methods for Constructing Simple Undirected Regular Graphs Based on Generalized de Bruijn Graphs Ryoya Ishii, Norikazu Takahashi (Okayama Univ.) NLP2017-90 |
The Generalized de Bruijn Graphs (GDBG) are a class of directed regular graphs. Since the average shortest path length o... [more] | NLP2017-90 pp.23-28 |
| NLP, CAS | 2017-10-06 10:30 |
Niigata | Machinaka Campus Nagaoka | Image Reconstruction by Nonnegative Matrix Factorization Hiromasa Kohno, Yuichi Tanji, Ken'ichi Fujimoto (Kagawa Univ.), Norikazu Takahashi (Okayama Univ.) CAS2017-34 NLP2017-59 |
[more] | CAS2017-34 NLP2017-59 pp.55-58 |
| NLP, CAS | 2017-10-06 13:00 |
Niigata | Machinaka Campus Nagaoka | Derivation of Global Clustering Coefficient Maximizing Graphs in the Case Where the Size is Close to the Order Ryoka Kuriki, Norikazu Takahashi (Okayama Univ.) CAS2017-37 NLP2017-62 |
The clustering coefficient is a measure of the tendency of vertices in a network to form clusters. It is known that many... [more] | CAS2017-37 NLP2017-62 pp.69-74 |
| NLP | 2017-07-13 13:00 |
Okinawa | Miyako Island Marine Terminal | A Newton-Type Algorithm for Nonnegative Matrix Factorization with Alpha-Divergence Satoshi Nakatsu, Norikazu Takahashi (Okayama Univ.) NLP2017-31 |
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix into two nonnegative f... [more] | NLP2017-31 pp.17-22 |
| NLP | 2017-05-11 15:35 |
Okayama | Okayama University of Science | A Pseudo-Decentralized Discrete-Time Algorithm for Estimating Algebraic Connectivity of Multiagent Networks Tomohisa Urakami, Norikazu Takahashi (Okayama Univ.) NLP2017-12 |
The algebraic connectivity of a network, which is defined as the second smallest eigenvalue of the Laplacian matrix, is ... [more] | NLP2017-12 pp.57-62 |
| NLP | 2017-05-11 16:00 |
Okayama | Okayama University of Science | Multiplicative Update Rules for Nonnegative Matrix Factorization with Regularization Terms Akihiro Koso, Norikazu Takahashi (Okayama Univ.) NLP2017-13 |
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix into two nonnegative f... [more] | NLP2017-13 pp.63-68 |
| IT, SIP, RCS | 2017-01-19 15:20 |
Osaka | Osaka City Univ. | Performance Evaluation of a Streaming Algorithm for Detecting Items with the Frequency of Appearance Changing Abruptly Tsuyoshi Kinoshita, Norikazu Takahashi (Okayama Univ.) IT2016-77 SIP2016-115 RCS2016-267 |
In recent years, a large amount of data is continuously generated at various places because of the development of inform... [more] | IT2016-77 SIP2016-115 RCS2016-267 pp.183-188 |
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