arXiv stat.ML
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A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
arXiv:2605.10493v3 Announce Type: replace-cross Abstract: This paper presents a PAC-Bayes framework for learning controllers for unknown stochastic linear discrete-time systems, where the system parameters are drawn from a fixed but unknown distribution. We derive a data-dependent high probability bound on the performa