Takabe Satoshi

Affiliation and department：
Job title： Associate Professor
Homepage URL (1)： https://isp.c.titech.ac.jp/

Research field (2)： Mathematical physics and basic theory , Soft computing

Research theme for competitive and other funds (5)：

2022 - 2026 Application of deep unfolding to stochastic information processing algorithms
2022 - 2025 深層展開に基づく信号処理アルゴリズム構築論の深化と展開
2019 - 2023 Mean-field theory for random geometric graph and its application to mathematical models
2017 - 2019 Statistical-mechanical approach for nonconvex compressed sensing and sparse modeling for correlated signals
2016 - 2019 Novel Development of Nonlinear Sparse Recovery

Papers (36)：

Ryo Hagiwara, Satoshi Takabe. Convergence Acceleration of Markov Chain Monte Carlo-Based Gradient Descent by Deep Unfolding. Journal of the Physical Society of Japan. 2024. 93. 6
Satoshi Takabe, Takashi Abe. Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection. IEEE Wireless Communications Letters. 2024. 13. 3. 701-705
Tadashi WADAYAMA, Satoshi TAKABE. Proximal Decoding for LDPC Codes. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2023. E106.A. 3. 359-367
Satoshi TAKABE, Tadashi WADAYAMA. Convergence Acceleration via Chebyshev Step: Plausible Interpretation of Deep-Unfolded Gradient Descent. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. 2022. E105.A. 8. 1110-1120
Tadashi Wadayama, Satoshi Takabe. Proximal Decoding for LDPC-coded Massive MIMO Channels. IEEE International Symposium on Information Theory - Proceedings. 2021. 2021-. 232-237

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MISC (26)：

萩原涼, 高邉賢史. Convergence Acceleration of MCMC-based Gradient Descent by Deep Unfolding. 日本物理学会講演概要集(CD-ROM). 2024. 79. 1
高邉賢史. A Study on Trainable MIMO Detector with Low Computational Complexity. 電子情報通信学会大会講演論文集(CD-ROM). 2023. 2023
河村祐弥, 高邉賢史. Convergence Acceleration of Particle-based Variational Inference by Deep Unfolding. 電子情報通信学会技術研究報告(Web). 2023. 123. 97(CAS2023 1-29)
高邉賢史. MIMO Signal Detection by Trainable Simulated Bifurcation Machine. 日本物理学会講演概要集(CD-ROM). 2023. 78. 2
阿部傑, 高邉賢史. Low-complexity Trainable M-QAM Signal Detector in Massive MIMO System. 情報理論とその応用シンポジウム予稿集(CD-ROM). 2023. 46th

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Lectures and oral presentations (45)：

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Work history (3)：

2021/09 - 現在 Tokyo Institute of Technology School of Computing Associate professor
2017/04 - 2021/08 Nagoya Institute of Technology Graduate School of Engineering Nagare College Assistant Professor
2017/10/01 - 2020/11 理化学研究所革新知能統合研究センター離散最適化ユニット客員研究員

Committee career (1)：

Awards (6)：

2023/06 - Paper Award Proximal Decoding for LDPC Codes
2021/08 - 電子情報通信学会信号処理研究会信号処理研究会賞
2019/03 - 電子情報通信学会信号処理研究会信号処理研究会賞
2018/10 - IEEE Information Theory Society IEEE Information Theory Society Japan Chapter Young Researcher Best Paper Award
2017/11 - 電子情報通信学会情報理論とその応用サブソサイエティ情報理論とその応用シンポジウム若手論文賞

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Association Membership(s) (4)：

日本オペレーションズ・リサーチ学会 , 電子情報通信学会 , IEEE , 日本物理学会

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