Sharper finite-sample OLS parameter error bounds for linear dynamical systems are obtained via a novel second-order martingale decomposition that achieves instance-optimal CLT rates up to constants in Frobenius norm.
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Proposes Bellman-sufficient state representations and information indices Y=χ(Ω) to organize sequential decision making with a conditional Bellman information-risk sandwich providing matching upper and lower complexity bounds.
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CLT-Optimal Parameter Error Bounds for Linear System Identification
Sharper finite-sample OLS parameter error bounds for linear dynamical systems are obtained via a novel second-order martingale decomposition that achieves instance-optimal CLT rates up to constants in Frobenius norm.
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Bellman-sufficient Information Complexity
Proposes Bellman-sufficient state representations and information indices Y=χ(Ω) to organize sequential decision making with a conditional Bellman information-risk sandwich providing matching upper and lower complexity bounds.