Sinkhorn divergence defines ambiguity sets that make distributionally robust linear quadratic control over linear policies solvable via convex programming even with safety constraints.
A system-level approach to controller synthesis
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A distributionally robust PAC-Bayesian approach derives sub-Gaussian loss proxies and performance bounds tied to closed-loop operator norms via system level synthesis, enabling optimization-based safety certificates for controllers facing sim-to-real gaps.
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Sinkhorn Ambiguity Sets for Distributionally Robust Control: Convexity, Weak Compactness, and Tractability
Sinkhorn divergence defines ambiguity sets that make distributionally robust linear quadratic control over linear policies solvable via convex programming even with safety constraints.
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Distributionally Robust PAC-Bayesian Control
A distributionally robust PAC-Bayesian approach derives sub-Gaussian loss proxies and performance bounds tied to closed-loop operator norms via system level synthesis, enabling optimization-based safety certificates for controllers facing sim-to-real gaps.