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新的PAC-Bayesian方法为二次系统提供控制认证

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种使用PAC-Bayesian界限来认证二次闭环控制系统的新方法。该方法通过采用系统级综合参数化来解决无界和非Lipschitz损失函数带来的挑战。该方法为控制响应上的后验分布提供了PAC-Bayes-Chernoff证书，并包含一个数据驱动的界限，该界限可以最小化以创建用于控制选择的学习算法。 AI

影响 这项研究可能导致更强大、可认证的AI驱动的控制系统，尤其是在数据有限的情况下。

排序理由 该集群包含一篇详细介绍控制系统新颖方法的学术论文。

在 arXiv cs.LG 阅读 →

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新的PAC-Bayesian方法为二次系统提供控制认证

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该集群包含一篇详细介绍控制系统新颖方法的学术论文。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Domagoj Herceg ·

    PAC-贝叶斯二次闭环控制证书

    arXiv:2606.28281v1 Announce Type: cross Abstract: PAC-Bayesian bounds provide finite-sample guarantees for data-dependent randomized predictors, but applying them to learning-based control is difficult because the natural objective is a quadratic trajectory cost. Such losses are …

  2. arXiv cs.LG TIER_1 English(EN) · Domagoj Herceg ·

    PAC-贝叶斯二次闭环控制证书

    PAC-Bayesian bounds provide finite-sample guarantees for data-dependent randomized predictors, but applying them to learning-based control is difficult because the natural objective is a quadratic trajectory cost. Such losses are unbounded, non-Lipschitz , and lead to response-de…

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