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Sotetsu KOYAMADA
Sotetsu KOYAMADA
Verified email at atr.jp
Title
Cited by
Cited by
Year
Suphx: Mastering mahjong with deep reinforcement learning
J Li, S Koyamada, Q Ye, G Liu, C Wang, R Yang, L Zhao, T Qin, TY Liu, ...
arXiv preprint arXiv:2003.13590, 2020
1602020
Deep learning of fMRI big data: a novel approach to subject-transfer decoding
S Koyamada, Y Shikauchi, K Nakae, M Koyama, S Ishii
arXiv preprint arXiv:1502.00093, 2015
832015
Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning
S Koyamada, S Okano, S Nishimori, Y Murata, K Habara, H Kita, S Ishii
Advances in Neural Information Processing Systems 36, 45716-45743, 2023
132023
Principal sensitivity analysis
S Koyamada, M Koyama, K Nakae, S Ishii
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 621-632, 2015
102015
Mjx: A framework for Mahjong AI research
S Koyamada, K Habara, N Goto, S Okano, S Nishimori, S Ishii
2022 IEEE Conference on Games (CoG), 504-507, 2022
32022
Neural Sequence Model Training via -divergence Minimization
S Koyamada, Y Kikuchi, A Kanemura, S Maeda, S Ishii
ICML Workshop on Learning to Generate Natural Language (LGNL 2017), 2017
12017
A Simple, Solid, and Reproducible Baseline for Bridge Bidding AI
H Kita, S Koyamada, Y Yamaguchi, S Ishii
arXiv preprint arXiv:2406.10306, 2024
2024
A Batch Sequential Halving Algorithm without Performance Degradation
S Koyamada, S Nishimori, S Ishii
arXiv preprint arXiv:2406.00424, 2024
2024
End-to-End Policy Gradient Method for POMDPs and Explainable Agents
S Nishimori, S Koyamada, S Ishii
arXiv preprint arXiv:2304.09769, 2023
2023
Reinforcement learning of communication strategy between players of the game of Contract Bridge
Y Yamaguchi, S Koyamada, K Nakae, S Ishii
IEICE Technical Report; IEICE Tech. Rep. 119 (381), 131-134, 2020
2020
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