Results 251 to 260 of about 241,763 (280)
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2018
In order to solve the problem that Q-learning can suffer from large overestimations in some stochastic environments, we first propose a new form of Q-learning, which proves that it is equivalent to the incremental form and analyze the reasons why the convergence rate of Q-learning will be affected by positive bias.
Zhihui Hu +3 more
openaire +1 more source
In order to solve the problem that Q-learning can suffer from large overestimations in some stochastic environments, we first propose a new form of Q-learning, which proves that it is equivalent to the incremental form and analyze the reasons why the convergence rate of Q-learning will be affected by positive bias.
Zhihui Hu +3 more
openaire +1 more source
Machine learning for microbiologists
Nature Reviews Microbiology, 2023Francesco Asnicar +2 more
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A guide to machine learning for biologists
Nature Reviews Molecular Cell Biology, 2021Joe G Greener +2 more
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Machine learning sheds light on microbial dark proteins
Nature Reviews Microbiology, 2023Aaron T Hammack, Crysten E Blaby-Haas
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Machine learning methods to model multicellular complexity and tissue specificity
Nature Reviews Materials, 2021Aaron K Wong, Olga G Troyanskaya
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Deep learning shapes single-cell data analysis
Nature Reviews Molecular Cell Biology, 2022Qin Ma, Dong Xu
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Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
IEEE Communications Surveys and Tutorials, 2021Latif U Khan, Walid Saad, Zhu Han
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