April 2022
Intermediate to advanced
376 pages
4h 55m
Japanese
Content preview from ゼロから作るDeep Learning ❹ ―強化学習編Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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参考文献
1章 バンディット問題
[1] Van der Maaten, Laurens, and Geoffrey Hinton. “Visualizing data using t-SNE.” Journal of machine learning research 9.11 (2008).
[2] Auer, Peter, Nicolo Cesa-Bianchi, and Paul Fischer. “Finite-time analysis of the multiarmed bandit problem.” Machine learning 47.2 (2002): 235-256.
[3] Williams, Ronald J. “Simple statistical gradient-following algorithms for connectionist reinforcement learning.” Machine learning 8.3 (1992): 229-256.
2章 マルコフ決定過程
[4] Csaba Szepesvari『速習 強化学習 ―基礎理論とアルゴリズム』（共立出版）
4章 動的計画法
[5] Sutton, Richard S., and Andrew G. Barto. “Reinforcement learning: An introduction.” MIT press, 2018.
7章 ニューラルネットワークとQ学習
[6] Duchi, John, Elad Hazan, and Yoram Singer. “Adaptive subgradient methods for online learning ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.