阻挠 发表于 2025-3-26 22:01:42

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过份艳丽 发表于 2025-3-27 04:59:51

Gaussian Process Regression with GPyTorch,uncertainty of the underlying objective function and an acquisition function that guides the search for the next sampling location based on its expected gain in the marginal utility. Efficiently calculating the posterior distributions becomes essential in the case of parallel Bayesian optimization a

nocturnal 发表于 2025-3-27 09:05:54

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overture 发表于 2025-3-27 11:41:00

Knowledge Gradient: Nested Optimization vs. One-Shot Learning,d modular design of the framework. This paves the way for many new acquisition functions we can plug in and test. In this chapter, we will extend our toolkit of acquisition functions to the knowledge gradient (KG), a nonmyopic acquisition function that performs better than expected improvement (EI)

敲竹杠 发表于 2025-3-27 16:47:13

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极力证明 发表于 2025-3-27 19:29:53

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闹剧 发表于 2025-3-28 00:43:17

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urethritis 发表于 2025-3-28 05:34:03

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transplantation 发表于 2025-3-28 11:57:34

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查看完整版本: Titlebook: Bayesian Optimization; Theory and Practice Peng Liu Book 2023 Peng Liu 2023 Python.Machine Learning.Bayesian optimization.hyper parameter