large deviations theory

Reduced Sample Complexity in Scenario-Based Control System Design via Constraint Scaling

  • Jaeseok Choi
  • Constantino Lagoa
  • Anirudh Subramanyam
    • Categories Control Applications, Convex Optimization, Stochastic Programming Tags , ,

    The scenario approach is widely used in robust control system design and chance-constrained optimization, maintaining convexity without requiring assumptions about the probability distribution of uncertain parameters. However, the approach can demand large sample sizes, making it intractable for safety-critical applications that require very low levels of constraint violation. To address this challenge, we propose a … Read more

    From Data to Decisions: Distributionally Robust Optimization is Optimal

  • Daniel Kuhn
  • Bart Paul Gerard Van Parys
  • Peyman Mohajerin Esfahani
    • Categories Robust Optimization, Second-Order Cone Programming, Stochastic Programming Tags , , , , ,

    We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transforms the data to an estimate of the expected cost function under the unknown data-generating distribution, … Read more