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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP, MSS | 2025-03-14 11:00 |
Okinawa | Miyakojima City Central Community Center (Okinawa) | Distributed Mini-Batch Stochastic Gradient Descent Method over Directed Networks for Non-Convex Optimization Problems Daichi Ishikawa, Naoki Hayashi, Masahiro Inuiguchi (Osaka Univ.) |
[more] | |
| NLP, MSS | 2025-03-14 18:00 |
Okinawa | Miyakojima City Central Community Center (Okinawa) | Distributed Online Proximal Gradient Method over Open Networks Masahiro Iida, Naoki Hayashi, Masahiro Inuiguchi (Osaka Univ.) |
[more] | |
| NLP, MSS | 2025-03-14 18:20 |
Okinawa | Miyakojima City Central Community Center (Okinawa) | Distributed Method for the Multiple Traveling Salesman Problem Considering Fairness Ryusei Matsuzaki, Daichi Ishikawa, Naoki Hayashi, Masahiro Inuiguchi (Osaka Univ.), Toshiaki Sawamura, Tomoyuki Maeda, Kei Morita, Yuya Hadano (Kobe Steel, Ltd.) |
[more] | |
| MSS, SS | 2025-01-12 14:05 |
Kagoshima | (Kagoshima) | MSS Roadmap 2025 : A Report on the Way Ichiro Toyoshima (TOSHIBA Energy Systems & Solutions), Ryosuke Adachi (Ymaguchi Univ.), Takafumi Kanazawa (Setsunan Univ.), Koichi Kobayashi (Hokkaido Univ.), Masaki Nakamura (Toyama Pref. Univ.), Naoki Hayashi (Osaka Univ.)  MSS2024-49 SS2024-28 |
[more] | MSS2024-49 SS2024-28 p.40 |
| LOIS, ICM | 2024-01-26 10:10 |
Nagasaki | Nagasaki Prefectural Art Museum (Nagasaki, Online) (Primary: On-site, Secondary: Online) |
Service Failure Detection Focusing on Simultaneous Increase in Various Types of Connection Retries in User Traffic Naoki Hayashi, Fumio Katayama, Naoki Tateishi, Osamu Okino, Mitsuho Tahara (NTT) ICM2023-34 LOIS2023-38 |
Many communication services are provided in carrier networks, and these communication services are realized by various e... [more] | ICM2023-34 LOIS2023-38 pp.33-38 |
| IT, ISEC, RCC, WBS | 2022-03-10 14:15 |
Online | Online (Online) | Distributed Online Optimization under Inequality Constraints on Directed Open Multi-agent Systems Riki Sawamura, Naoki Hayashi, Masahiro Inuiguchi (Osaka Univ.) IT2021-108 ISEC2021-73 WBS2021-76 RCC2021-83 |
Distributed optimization in multi-agent systems has attracted attention in various fields. In this study, we consider a ... [more] | IT2021-108 ISEC2021-73 WBS2021-76 RCC2021-83 pp.150-154 |
| ICM | 2021-07-16 10:00 |
Online | Online (Online) | Event Correlation Method with Bayesian Network Atsushi Takada, Naoki Hayashi, Ryosuke Sato, Toshihiko Seki, Kyoko Yamagoe (NTT) ICM2021-15 |
Nowadays, research has been conducted to automate the operation of IT services using AI and orchestrator. In the operati... [more] | ICM2021-15 pp.28-33 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-14 11:20 |
Online | Online (Online) | Model Predictive Control with Robust Constraint Satisfaction Using Gaussian Process Wataru Hashimoto, Naoki Hayashi, Shigemasa Takai (Osaka Univ) RCC2021-24 |
[more] | RCC2021-24 pp.13-16 |
| RCC | 2021-01-22 13:55 |
Online | Online (Online) | Distributed Mini-Batch Stochastic Subgradient Algorithm over Directed Networks Daichi Ishikawa, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) RCC2020-35 |
We consider a constrained optimization problem of minimizing the sum of the local convex objective function values of ag... [more] | RCC2020-35 pp.4-8 |
| MSS, CAS, IPSJ-AL [detail] | 2020-11-25 16:10 |
Online | Online (Online) | Distributed convex optimization with inequality constraints over directed graphs based on row stochasticity Hiroaki Sakuma, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) CAS2020-22 MSS2020-14 |
Distributed optimization is a method in which agents exchange information on the network to obtain the optimal solution ... [more] | CAS2020-22 MSS2020-14 pp.16-21 |
| ICM | 2020-07-16 12:55 |
Online | Online (Online) | Configuration management method by adding traffic considering network load Mizuto Nakamura, Naoki Hayashi, Atsushi Takada, Toshihiko Seki, Kyoko Yamagoe (NTT) ICM2020-9 |
[more] | ICM2020-9 pp.7-12 |
| ICM, IPSJ-CSEC, IPSJ-IOT | 2020-05-14 13:15 |
Online | Online (Online) | Topology Discovery Method with Alarm Information for Telecom Network Atsushi Takada, Naoki Hayashi, Mizuto Nakamura, Naoyuki Tanji, Toshihiko Seki, Kyoko Yamagoe (NTT) ICM2020-1 |
[more] | ICM2020-1 pp.1-6 |
| RCC | 2020-01-27 14:10 |
Osaka | (Osaka) | Distributed online subgradient method over unbalanced directed graphs Makoto Yamashita, Naoki Hayashi, Takeshi Hatanaka, Shigemasa Takai (Osaka Univ.) RCC2019-72 |
This paper considers a constrained distributed online optimization problem over strongly connected unbalanced directed n... [more] | RCC2019-72 pp.13-18 |
| RCC, ITS, WBS | 2019-11-06 13:50 |
Nara | Nara Institute of Science and Technology (Nara) | A Preliminary Study on Distributed LQ Control Approach for Blade Pitch Angle Control of Floating Offshore Wind Farm Wataru Hashimoto, Naoki Hayashi (Osaka Univ), Naoyuki Hara (Osaka Pref Univ), Shigemasa Takai (Osaka Univ) WBS2019-33 ITS2019-24 RCC2019-64 |
[more] | WBS2019-33 ITS2019-24 RCC2019-64 pp.53-57 |
| SeMI, RCS, NS, SR, RCC (Joint) |
2019-07-10 11:35 |
Osaka | I-Site Nanba（Osaka） (Osaka) | Distributed Convex Optimization by Consensus ADMM with Communication Time-Delays Kazuma Tanaka, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) RCC2019-13 |
[more] | RCC2019-13 pp.11-14 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) (Hokkaido) | [Poster Presentation]
Variational Approximation Accuracy in Non-negative Matrix Factorization Naoki Hayashi (MSI) IBISML2018-51 |
The asymptotic behavior of the variational free energy of the non-negative matrix factorization (NMF) has been elucidate... [more] | IBISML2018-51 pp.53-60 |
| MBE, NC (Joint) |
2018-03-14 10:25 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Tokyo) | Experimental Analysis of Real Log Canonical Threshold in Stochastic Matrix Factorization using Hamiltonian Monte Carlo Method Naoki Hayashi, Sumio Watanabe (Tokyo Tech) NC2017-89 |
For the real log canonical threshold (RLCT) that gives the Bayesian generalization error of stochastic matrix factorizat... [more] | NC2017-89 pp.127-131 |
| MSS, NLP (Joint) |
2018-03-12 14:25 |
Osaka | (Osaka) | Analysis of Distributed Cooperative Thompson Sampling Motoki Kamimura, Naoki Hayashi, Shigemasa Takai (Osaka Univ.) MSS2017-80 |
The bandit problem is a mathematical model which formulates the trade-off between the exploration for the better strateg... [more] | MSS2017-80 pp.15-20 |
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo (Tokyo) | [Poster Presentation]
Real Log Canonical Threshold of Stochastic Matrix Factorization and its Application to Bayesian Learning Naoki Hayashi, Sumio Watanabe (TokyoTech) IBISML2017-38 |
In stochastic matrix factorization (SMF), we deal with problems that we predict an observed stochastic matrix as a produ... [more] | IBISML2017-38 pp.23-30 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2017-09-15 10:30 |
Tokyo | (Tokyo) | Experimental Analysis of Variational Bayesian Method in Model Selection of Gaussian Mixture Model by Singular Bayesian Information Criterion Naoki Hayashi (Tokyo Tech), Fumito Nakamura (Bosch) PRMU2017-41 IBISML2017-13 |
A Gaussian mixture model (GMM) is a statistical model used in various fields such a pattern recognition, thus, it is imp... [more] | PRMU2017-41 IBISML2017-13 pp.19-26 |
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