Honda, Junya(Graduate School of Informatics, Department of Informatics) | Activity Database on Education and Research, Kyoto University

Honda, Junya

Graduate School of Informatics, Department of Informatics Associate Professor

Last Updated :2025/05/27

Basic Information

Faculty

工学部

Academic Degree

修士（情報理工学）(東京大学)

博士（科学）(東京大学)

Academic Resume (Graduate Schools)

東京大学, 大学院情報理工学系研究科数理情報学専攻修士課程, 修了

東京大学, 大学院新領域創成科学研究科複雑理工学専攻博士課程, 修了

Academic Resume (Undergraduate School/Majors)

東京大学, 工学部計数工学科, 卒業

Research History

From Jan. 2021, To Present
Kyoto University, Department of Systems Science, Graduate School of Informatics, Associate Professor

From Jan. 2017, To Dec. 2020
The University of Tokyo, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, Lecturer

From Mar. 2013, To Dec. 2016
The University of Tokyo, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, Research Associate

ID,URL

J-Global ID
202001010142324778

researchmap URL

https://researchmap.jp/jhonda

Last Updated :2025/05/27

Research

Research Topics, Overview of the research

Research Topics
Machine learning, bandit problems, reinforcement learning.
Overview of the research
We are researching online decision making problems in machine learning such as bandit problems and reinforcement learning. For these topics we are studying construction of good algorithms and their limitations from theoretical and practical viewpoints.

Papers

Active model selection: A variance minimization approach
Satoshi Hara; Mitsuru Matsuura; Junya Honda; Shinji Ito
Machine Learning, 21 Nov. 2024

Learning with Posterior Sampling for Revenue Management under Time-varying Demand.
Kazuma Shimizu; Junya Honda; Shinji Ito; Shinji Nakadai
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence(IJCAI), 2024

Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring.
Taira Tsuchiya; Shinji Ito; Junya Honda
Forty-first International Conference on Machine Learning(ICML), 2024

Spatiotemporal dynamics of odor representations in the human brain revealed by EEG decoding
Mugihiko Kato; Toshiki Okumura; Yasuhiro Tsubo; Junya Honda; Masashi Sugiyama; Kazushige Touhara; Masako Okamoto
Proceedings of the National Academy of Sciences, 24 May 2022, Peer-reviewed

Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds.
Jongyeong Lee; Junya Honda; Shinji Ito; Min-hwan Oh
COLT, 2024

Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds.
Shinji Ito; Taira Tsuchiya; Junya Honda
COLT, 2024

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds.
Taira Tsuchiya; Shinji Ito; Junya Honda
NeurIPS, 2023

Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits.
Jongyeong Lee; Junya Honda; Chao-Kai Chiang; Masashi Sugiyama
ICML, 2023

Thompson Exploration with Best Challenger Rule in Best Arm Identification.
Jongyeong Lee; Junya Honda; Masashi Sugiyama
ACML, 2023

Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits.
Taira Tsuchiya; Shinji Ito; Junya Honda
AISTATS, 2023

Best-of-Both-Worlds Algorithms for Partial Monitoring.
Taira Tsuchiya; Shinji Ito; Junya Honda
ALT, 2023, Peer-reviewed

Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems.
Junya Honda; Shinji Ito; Taira Tsuchiya
ALT, 2023, Peer-reviewed

Bayesian optimization with partially specified queries.
Shogo Hayashi; Junya Honda; Hisashi Kashima
Machine Learning, 2022, Peer-reviewed

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification.
Junpei Komiyama; Taira Tsuchiya; Junya Honda
NeurIPS, 2022, Peer-reviewed

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs.
Shinji Ito; Taira Tsuchiya; Junya Honda
NeurIPS, 2022, Peer-reviewed

Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds.
Shinji Ito; Taira Tsuchiya; Junya Honda
COLT, 2022, Peer-reviewed

Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions.
Charles Riou; Junya Honda
Algorithmic Learning Theory(ALT), 2020, Peer-reviewed

Optimal dose escalation methods using deep reinforcement learning in phase I oncology trials.
Kentaro Matsuura; Kentaro Sakamaki; Junya Honda; Takashi Sozu
Journal of biopharmaceutical statistics, 30 Jan. 2023, Peer-reviewed

Polynomial-time Algorithms for Combinatorial Pure Exploration with Full-bandit Feedback.
Yuko Kuroki; Liyuan Xu; Atsushi Miyauchi 0001; Junya Honda; Masashi Sugiyama
CoRR, 2019

Optimal adaptive allocation using deep reinforcement learning in a dose-response study.
Kentaro Matsuura; Junya Honda; Imad El Hanafi; Takashi Sozu; Kentaro Sakamaki
Statistics in medicine, 07 Nov. 2021, Peer-reviewed

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences.
Ikko Yamane; Junya Honda; Florian Yger; Masashi Sugiyama
Proceedings of the 38th International Conference on Machine Learning(ICML), 2021, Peer-reviewed

Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring.
Taira Tsuchiya; Junya Honda; Masashi Sugiyama
Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020(NeurIPS), 2020, Peer-reviewed

Online Dense Subgraph Discovery via Blurred-Graph Feedback.
Yuko Kuroki; Atsushi Miyauchi 0001; Junya Honda; Masashi Sugiyama
Proceedings of the 37th International Conference on Machine Learning(ICML), 2020, Peer-reviewed

Polynomial-Time Algorithms for Multiple-Arm Identification with Full-Bandit Feedback.
Yuko Kuroki; Liyuan Xu; Atsushi Miyauchi 0001; Junya Honda; Masashi Sugiyama
Neural Comput., 2020, Peer-reviewed

A bad arm existence checking problem: How to utilize asymmetric problem structure?
Tabata, Koji; Nakamura, Atsuyoshi; Honda, Junya; Komatsuzaki, Tamiki
MACHINE LEARNING, Oct. 2019, Peer-reviewed

Good arm identification via bandit feedback
Hideaki Kano; Junya Honda; Kentaro Sakamaki; Kentaro Matsuura; Atsuyoshi Nakamura; Masashi Sugiyama
MACHINE LEARNING, May 2019, Peer-reviewed

Uncoupled Regression from Pairwise Comparison Data.
Liyuan Xu; Junya Honda; Gang Niu; Masashi Sugiyama
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS), 2019, Peer-reviewed

On the Calibration of Multiclass Classification with Rejection.
Chenri Ni; Nontawat Charoenphakdee; Junya Honda; Masashi Sugiyama
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019(NeurIPS), 2019, Peer-reviewed

Learning from Positive and Unlabeled Data with a Selection Bias.
Masahiro Kato; Takeshi Teshima; Junya Honda
7th International Conference on Learning Representations, 2019, Peer-reviewed

Unsupervised Domain Adaptation Based on Source-Guided Discrepancy
Seiichi Kuroki; Nontawat Charoenphakdee; Han Bao; Junya Honda; Issei Sato; Masashi Sugiyama
THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2019, Peer-reviewed

Dueling Bandits with Qualitative Feedback
Liyuan Xu; Junya Honda; Masashi Sugiyama
THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2019, Peer-reviewed

Exploring a potential energy surface by machine learning for characterizing atomic transport
Kanamori, Kenta; Toyoura, Kazuaki; Honda, Junya; Hattori, Kazuki; Seko, Atsuto; Karasuyama, Masayuki; Shitara, Kazuki; Shiga, Motoki; Kuwabara, Akihide; Takeuchi, Ichiro
PHYSICAL REVIEW B, Mar. 2018, Peer-reviewed

Nonconvex Optimization for Regression with Fairness Constraints.
Junpei Komiyama; Akiko Takeda; Junya Honda; Hajime Shimao
Proceedings of the 35th International Conference on Machine Learning(ICML), 2018, Peer-reviewed

A fully adaptive algorithm for pure exploration in linear bandits.
Liyuan Xu; Junya Honda; Masashi Sugiyama
International Conference on Artificial Intelligence and Statistics(AISTATS), 2018, Peer-reviewed

Normal Bandits of Unknown Means and Variances
Cowan, Wesley; Honda, Junya; Katehakis, Michael N.
JOURNAL OF MACHINE LEARNING RESEARCH, 2018, Peer-reviewed

Exact Asymptotics of Random Coding Error Probability for General Memoryless Channels
Honda, Junya
2018 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2018, Peer-reviewed

Worst-case Redundancy of Optimal Binary AIFV Codes and Their Extended Codes
Hu, Weihua; Yamamoto, Hirosuke; Honda, Junya
IEEE TRANSACTIONS ON INFORMATION THEORY, Aug. 2017, Peer-reviewed

Variable-to-Fixed Length Homophonic Coding Suitable for Asymmetric Channel Coding
Honda, Junya; Yamamoto, Hirosuke
2017 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2017, Peer-reviewed

Position-based Multiple-play Bandit Problem with Unknown Position Bias.
Junpei Komiyama; Junya Honda; Akiko Takeda
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), 2017, Peer-reviewed

Copeland Dueling Bandit Problem: Regret Lower Bound, Optimal Algorithm, and Computationally Efficient Algorithm.
Junpei Komiyama; Junya Honda; Hiroshi Nakagawa
Proceedings of the 33nd International Conference on Machine Learning(ICML), 2016, Peer-reviewed

Variable-to-Fixed Length Homophonic Coding with a Modified Shannon-Fano-Flias Code
Honda, Junya; Yamamoto, Hirosuke
PROCEEDINGS OF 2016 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS (ISITA 2016), 2016, Peer-reviewed

Tight Upper Bounds on the Redundancy of Optimal Binary AIFV Codes
Hu, Weihua; Yamamoto, Hirosuke; Honda, Junya
2016 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, 2016, Peer-reviewed

Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Reward
Honda, Junya; Takemura, Akimichi
JOURNAL OF MACHINE LEARNING RESEARCH, Dec. 2015, Peer-reviewed

Almost Instantaneous Fixed-to-Variable Length Codes
Yamamoto, Hirosuke; Tsuchihashi, Masato; Honda, Junya
IEEE TRANSACTIONS ON INFORMATION THEORY, Dec. 2015, Peer-reviewed

Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays.
Junpei Komiyama; Junya Honda; Hiroshi Nakagawa
Proceedings of the 32nd International Conference on Machine Learning(ICML), 2015, Peer-reviewed

Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem.
Junpei Komiyama; Junya Honda; Hisashi Kashima; Hiroshi Nakagawa
Proceedings of The 28th Conference on Learning Theory(COLT), 2015, Peer-reviewed

Exact Asymptotics for the Random Coding Error Probability
Honda, Junya
2015 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2015, Peer-reviewed

Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring
Komiyama, Junpei; Honda, Junya; Nakagawa, Hiroshi
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 28 (NIPS 2015), 2015, Peer-reviewed

FV Polar Coding for Lossy Compression with an Improved Exponent
Wang, Runxin; Honda, Junya; Yamamoto, Hirosuke; Liu, Rongke
2015 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2015, Peer-reviewed

Construction of Polar Codes for Channels with Memory
Wang, Runxin; Honda, Junya; Yamamoto, Hirosuke; Liu, Rongke; Hou, Yi
2015 IEEE INFORMATION THEORY WORKSHOP - FALL (ITW), 2015, Peer-reviewed

Variable Length Lossy Coding Using an LDPC Code
Honda, Junya; Yamamoto, Hirosuke
IEEE TRANSACTIONS ON INFORMATION THEORY, Jan. 2014, Peer-reviewed

Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors
Honda, Junya; Takemura, Akimichi
ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 33, 2014, Peer-reviewed

RSA Meets DPA: Recovering RSA Secret Keys from Noisy Analog Data
Kunihiro, Noboru; Honda, Junya
CRYPTOGRAPHIC HARDWARE AND EMBEDDED SYSTEMS - CHES 2014, 2014, Peer-reviewed

Polar Coding Without Alphabet Extension for Asymmetric Models
Honda, Junya; Yamamoto, Hirosuke
IEEE TRANSACTIONS ON INFORMATION THEORY, Dec. 2013, Peer-reviewed

Stochastic bandit based on empirical moments
Junya Honda; Akimichi Takemura
Journal of Machine Learning Research, 2012, Peer-reviewed

Polar Coding without Alphabet Extension for Asymmetric Channels
Honda, Junya; Yamamoto, Hirosuke
2012 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY PROCEEDINGS (ISIT), 2012, Peer-reviewed

Fast Linear-Programming Decoding of LDPC Codes over GF(2(m))
Honda, Junya; Yamamoto, Hirosuke
2012 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS (ISITA 2012), 2012, Peer-reviewed

An asymptotically optimal policy for finite support models in the multiarmed bandit problem
Honda, Junya; Takemura, Akimichi
MACHINE LEARNING, Dec. 2011, Peer-reviewed

An asymptotically optimal bandit algorithm for bounded support models
Junya Honda; Akimichi Takemura
COLT 2010 - The 23rd Conference on Learning Theory, 2010, Peer-reviewed

Variable Length Lossy Coding using an LDPC Code
Honda, Junya; Yamamoto, Hirosuke
2009 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, VOLS 1- 4, 2009, Peer-reviewed

Application of LCLP to Lossy Source Coding
Miyake, Shigeki; Honda, Junya; Yamamoto, Hirosuke
2008 INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY AND ITS APPLICATIONS, VOLS 1-3, 2008, Peer-reviewed

Misc.

Construction of Almost Instantaneous FV codes based on Integer Programming
TSUCHIHASHI Masato; YAMAMOTO Hirosuke; HONDA Junya
IEICE technical report. Information theory, 17 Jul. 2014

Variable Length Coding of Asymmetric Channels using a Homophonic Code
HONDA Junya; YAMAMOTO Hirosuke
IEICE technical report. Information theory, 12 Jul. 2012

On a Non-asymptotic Analysis Using Large Deviation Principles in the Multiarmed Bandit Problem
HONDA Junya; TAKEMURA Akimichi
電子情報通信学会技術研究報告. IBISML, 情報論的学習理論と機械学習 = IEICE technical report. IBISML, Information-based induction sciences and machine learning, 12 Jun. 2012

Bad Arm Existence Checking Algorithms with Small Sample Complexity
田畑公次; 中村篤祥; 本多淳也; 小松崎民樹
人工知能基本問題研究会, 16 Mar. 2018

Source Coding with LDPC Code using Linear Programming
HONDA Junya; MIYAKE Shigeki; YAMAMOTO Hirosuke; MARUYAMA Mitsuru
IEICE technical report, 17 Jul. 2008

Books and Other Publications

バンディット問題の理論とアルゴリズム = Theory and algorithms for bandit problems
本多, 淳也; 中村, 篤祥; 講談社サイエンティフィク
講談社, 2016
Find Kyoto University's collection of books :

External funds: Kakenhi

バンディット問題における最適性達成のためのランダム方策の発展と解析
Grant-in-Aid for Scientific Research (C)
Basic Section 60010:Theory of informatics-related
Kyoto University
本多淳也
From 01 Apr. 2021, To 31 Mar. 2025, Granted
機械学習;バンディット問題;オンライン学習;治験;学習理論;実験計画;情報理論
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21K11747/

Construction of knowledge discovery algorithms based on information theoretic methods
Grant-in-Aid for Early-Career Scientists
Basic Section 60010:Theory of informatics-related
Kyoto University;The University of Tokyo
Junya Honda
From 01 Apr. 2018, To 31 Mar. 2021, Project Closed
機械学習;情報理論;バンディット問題
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18K17998/

確率モデルに基づいた結晶構造の学習および推定法の確立
Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
Science and Engineering
The University of Tokyo
本多淳也
From 01 Apr. 2016, To 31 Mar. 2018, Project Closed
機械学習;実験計画法;材料探索;材料科学;計算物理
https://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-16H00881/

効率的な材料探索のための実験計画法の開発
Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
Science and Engineering
The University of Tokyo
本多淳也
From 01 Apr. 2014, To 31 Mar. 2016, Project Closed
機械学習
https://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-26106506/

多腕バンディット問題における最適戦略の構成と発展
Grant-in-Aid for Research Activity Start-up
The University of Tokyo
本多淳也
From 30 Aug. 2013, To 31 Mar. 2015, Declined
機械学習;統計学;多腕バンディット問題
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-25880006/

多様な環境に同時最適となる頑健な動的意思決定方策の基盤技術
Grant-in-Aid for Scientific Research (B)
Basic Section 61030:Intelligent informatics-related
Kyoto University
本多淳也
From 01 Apr. 2025, To 31 Mar. 2030, Adopted
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-25K03184/

Last Updated :2025/05/27

Education

Teaching subject(s)

From 01 Apr. 2024, To 31 Mar. 2025
Mathematical theory of information and communications
9142, Fall, Faculty of Engineering, 2

From 01 Apr. 2024, To 31 Mar. 2025
Introduction to Applied Mathematics and Physics
9114, Spring, Faculty of Engineering, 2

From 01 Apr. 2024, To 31 Mar. 2025
Stochastic Discrete Event Systems
9096, Spring, Faculty of Engineering, 2

From 01 Apr. 2024, To 31 Mar. 2025
Systems Science, Advanced II
3512, Fall, Graduate School of Informatics, 2

From 01 Apr. 2024, To 31 Mar. 2025
Systems Science, Advanced I
3542, Spring, Graduate School of Informatics, 2

From 01 Apr. 2024, To 31 Mar. 2025
Statistical Systems Theory
3536, Spring, Graduate School of Informatics, 2

From 01 Apr. 2024, To 31 Mar. 2025
Statistical Systems Theory
M310, Spring, Institute for Liberal Arts and Sciences, 2

From 01 Apr. 2023, To 31 Mar. 2024
Stochastic Discrete Event Systems
9096, Spring, Faculty of Engineering, 2

From 01 Apr. 2023, To 31 Mar. 2024
Mathematical theory of information and communications
9142, Fall, Faculty of Engineering, 2

From 01 Apr. 2023, To 31 Mar. 2024
Systems Science, Advanced I
3542, Spring, Graduate School of Informatics, 2

From 01 Apr. 2023, To 31 Mar. 2024
Statistical Systems Theory
3536, Spring, Graduate School of Informatics, 2

From 01 Apr. 2023, To 31 Mar. 2024
Systems Science, Advanced II
3512, Fall, Graduate School of Informatics, 2

From 01 Apr. 2023, To 31 Mar. 2024
ILAS Seminar
Z001, Spring, Institute for Liberal Arts and Sciences, 2

From 01 Apr. 2023, To 31 Mar. 2024
Statistical Systems Theory
M310, Spring, Institute for Liberal Arts and Sciences, 2

From 01 Apr. 2022, To 31 Mar. 2023
Mathematical theory of information and communications
9142, Fall, Faculty of Engineering, 2

From 01 Apr. 2022, To 31 Mar. 2023
Seminar on Applied Mathematics and Physics
9074, Fall, Faculty of Engineering, 2

From 01 Apr. 2022, To 31 Mar. 2023
Systems Science, Advanced I
3542, Spring, Graduate School of Informatics, 2

From 01 Apr. 2022, To 31 Mar. 2023
Systems Science, Advanced II
3512, Fall, Graduate School of Informatics, 2

From 01 Apr. 2022, To 31 Mar. 2023
Statistical Systems Theory
3536, Spring, Graduate School of Informatics, 2

From 01 Apr. 2022, To 31 Mar. 2023
Statistical Systems Theory
M310, Spring, Institute for Liberal Arts and Sciences, 2

From 01 Apr. 2022, To 31 Mar. 2023
Stochastic Discrete Event Systems
9096, Spring, Faculty of Engineering, 2

From Apr. 2021, To Mar. 2022
Mathematical theory of information and communications
Fall, 工学部

From Apr. 2021, To Mar. 2022
Stochastic Discrete Event Systems
Spring, 工学部

From Apr. 2021, To Mar. 2022
Systems Science, Advanced II
Fall, 情報学研究科

From Apr. 2021, To Mar. 2022
Systems Science, Advanced I
Spring, 情報学研究科

From Apr. 2021, To Mar. 2022
Statistical Systems Theory
Spring, 情報学研究科

Participation in PhD Defense

Environment Adaptive Regret Analysis in Bandit Problems
TSUCHIYA TAIRA, Graduate School of Informatics, Chief Examiner
25 Sep. 2023

Convergence Formulas for the Level-increment Truncation Approximation of M/G/1-type Markov Chains
OUCHI KATSUHISA, Graduate School of Informatics, Sub-chief Examiner
24 Nov. 2023

Last Updated :2025/05/27

Administration

Faculty management (title, position)

From 01 Apr. 2021, To 31 Mar. 2023
広報WG委員

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