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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE (Joint) |
2025-03-06 16:20 |
Tokyo | (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Global Convergence Analysis of Distributed Lasso Algorithm based on Alternating Direction Method of Multipliers Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) |
[more] | |
| NC, MBE (Joint) |
2025-03-06 16:45 |
Tokyo | (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Distributed Sequential Minimal Optimization Algorithm for Support Vector Machines Zhifu Xu, Ryota Yamada, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) |
[more] | |
| NLP, CAS | 2024-10-17 10:40 |
Tottori | Information Center, Tottori University (Tottori) | Distributed Sequential Minimal Optimization Algorithm for Linear Support Vector Machines Zhifu Xu, Kim Saidi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.)  CAS2024-30 NLP2024-60 |
In this report, we propose a distributed Sequential Minimal Optimization (SMO) algorithm for multiple agents communicati... [more] | CAS2024-30 NLP2024-60 pp.16-20 |
| NLP, CAS | 2024-10-18 14:50 |
Tottori | Information Center, Tottori University (Tottori) | An Extension of Multiplicative Update Rule for Nonnegative Matrix Factorization Yuma Okazaki, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2024-57 NLP2024-87 |
Nonnegative Matrix Factorization (NMF) is the process of decomposing a given nonnegative matrix into two nonnegative fac... [more] | CAS2024-57 NLP2024-87 pp.150-155 |
| NLP | 2024-05-09 15:30 |
Kagawa | Kagawa Prefecture Social Welfare Center (Kagawa) | An Euclidean Steiner Tree Problem Solver based on Genetic Algorithm and Delaunay Triangulation Liping Zhang, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2024-6 |
In this report, we propose an approach based on the genetic algorithm and the Delaunay triangulation for solving the Euc... [more] | NLP2024-6 pp.25-30 |
| NLP | 2024-05-10 10:30 |
Kagawa | Kagawa Prefecture Social Welfare Center (Kagawa) | Federated Learning Algorithms based on Decentralized Spanning Tree Generation and Step-by-Step Consensus Yuki Mori, Tatsuya Kayatani, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2024-11 |
A large amount of high-quality data is necessary to improve the learning accuracy of neural networks. However, there are... [more] | NLP2024-11 pp.52-57 |
| NLP, MSS | 2024-03-14 10:00 |
Misc. | Kikai-Shinko-Kaikan Bldg. (Misc.) | Extraction of Traffic Accident High-Risk Areas Using Deep Learning of Map Images and Grad-CAM Kaito Arase, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2023-86 NLP2023-138 |
An attempt has been made to predict the traffic accident risk of each map tile image at zoom level 17 using a Convolutio... [more] | MSS2023-86 NLP2023-138 pp.71-76 |
| NLP, MSS | 2024-03-14 11:15 |
Misc. | Kikai-Shinko-Kaikan Bldg. (Misc.) | Parallelization of a Search Algorithm for Regular Graphs with Minimum Average Shortest Path Length Taku Hirayama, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2023-89 NLP2023-141 |
Computer networks in data centers are modeled as regular graphs, and the average shortest path length (ASPL) of such a g... [more] | MSS2023-89 NLP2023-141 pp.87-92 |
| NLP, CAS | 2023-10-07 13:00 |
Gifu | Work plaza Gifu (Gifu) | An algorithm for finding regular graphs that maximize algebraic connectivity under a specified number of vertices and degree Masashi Kurahashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2023-54 NLP2023-53 |
Algebraic connectivity is a measure of network robustness, and defined by the second smallest eigenvalue of the Laplacia... [more] | CAS2023-54 NLP2023-53 pp.106-110 |
| NLP, CAS | 2023-10-07 13:20 |
Gifu | Work plaza Gifu (Gifu) | Proposal and evaluation of a distributed lasso algorithm based on alternating direction multiplier method Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2023-55 NLP2023-54 |
Lasso is widely known as a sparse estimation method for regression coefficients in linear regression models, and the Alt... [more] | CAS2023-55 NLP2023-54 pp.111-116 |
| WPT, EMCJ, EMD (Joint) |
2023-07-21 16:30 |
Tokyo | (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Determination of Circuit Element Constant Ranges by ANN for EMI Filters in Brush Motor Circuits Containing Cables Shohei Kan, Norikazu Takahashi, Masaki Himuro, Akito Mashino, Kengo Iokibe, Yoshitaka Toyota (Okayama Univ.) EMCJ2023-34 |
[more] | EMCJ2023-34 pp.29-32 |
| PRMU, IPSJ-CVIM | 2023-05-19 10:05 |
Aichi | (Aichi, Online) (Primary: On-site, Secondary: Online) |
Differentiable Ray Tracing for Estimating Object Shape, Texture, and Light Source Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) PRMU2023-10 |
In this report, an inverse problem of raytracing-based image synthesis is discussed. The proposed method estimates a se... [more] | PRMU2023-10 pp.51-56 |
| NLP, MSS | 2023-03-17 14:30 |
Nagasaki | (Nagasaki, Online) (Primary: On-site, Secondary: Online) |
Global Convergence Analysis of Distributed HALS Algorithm for Nonnegative Matrix Factorization Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-104 NLP2022-149 |
As a fast computational method for Nonnegative Matrix Factorization (NMF), the Hierarchical Alternating Least Squares ... [more] |
MSS2022-104 NLP2022-149 pp.198-203 |
| NLP, MSS | 2023-03-17 14:50 |
Nagasaki | (Nagasaki, Online) (Primary: On-site, Secondary: Online) |
Reformulation of Optimization Problem in Randomized NMF and Proposal of A Novel Iterative Update Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-105 NLP2022-150 |
As an approach to efficiently perform large-scale Nonnegative Matrix Factorization (NMF), a randomized NMF was recently ... [more] | MSS2022-105 NLP2022-150 pp.204-209 |
| CCS, NLP | 2022-06-09 17:15 |
Osaka | (Osaka, Online) (Primary: On-site, Secondary: Online) |
Visualization of decisions from CNN models trained on OpenStreetMap images labeled based on traffic accident data Kaito Arase, Zhijian Wu, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2022-10 CCS2022-10 |
The authors have recently conducted training of Convolutional Neural Networks (CNNs) on OpenStreetMap images each of whi... [more] | NLP2022-10 CCS2022-10 pp.46-51 |
| CCS, NLP | 2022-06-09 17:40 |
Osaka | (Osaka, Online) (Primary: On-site, Secondary: Online) |
Speeding up an algorithm for searching generalized Moore graphs Taku Hirayama, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2022-11 CCS2022-11 |
Computer networks in data centers are modeled as undirected regular graphs, and the average shortest path length (ASPL) ... [more] | NLP2022-11 CCS2022-11 pp.52-57 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 13:50 |
Online | Online (Online) | Simplification of Average Consensus Algorithm in Distributed HALS Algorithm for NMF Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-3 IBISML2021-3 |
Nonnegative Matrix Factorization (NMF) is the process of approximating a given nonnegative matrix by the product of two ... [more] | NC2021-3 IBISML2021-3 pp.15-22 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 14:15 |
Online | Online (Online) | Modification of Optimization Problem in Randomized NMF and Design of Optimization Method based on HALS Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-4 IBISML2021-4 |
Nonnegative matrix factorization (NMF) is the process of decomposing a given nonnegative matrix into two nonnegative fac... [more] | NC2021-4 IBISML2021-4 pp.23-30 |
| NLP, MSS (Joint) |
2021-03-15 13:00 |
Online | Online (Online) | Proposal of Novel Distributed Learning Algorithms for Multi-Neural Networks Kazuaki Harada, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-58 |
A method for multiple neural networks (NNs) with the same structure to learn multiple sets of training data collected at... [more] | NLP2020-58 pp.17-22 |
| NLP, MSS (Joint) |
2021-03-15 13:25 |
Online | Online (Online) | Graph Structure Optimization Using Genetic Algorithms Hiroki Tajiri, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-59 |
There are many large and complex networks in the real world. These networks are modeled as graphs and analyzed using a v... [more] | NLP2020-59 pp.23-28 |
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