Conjugate convex functions in optimal stochastic control

Optimal Stochastic Quadrature Formulas For Convex Functions

We study optimal stochastic (or Monte Carlo) quadrature formulas for convex functions. While nonadaptive Monte Carlo methods are not better than deterministic methods we prove that adaptive Monte Carlo methods are much better. Abstract. We study optimal stochastic (or Monte Carlo) quadrature formulas for convex functions. While nonadaptive Monte Carlo methods are not better than deter-ministic ...

Conjugate convex functions, duality, and optimal control problems I: Systems governed by ordinary differential equations

This paper presents a general and complete duality theory for optimal control of systems governed by linear ordinary differential equations with a convex cost criterion. Existence theorems for optimal control problems are obtained using the duality theory and a direct relationship between duality and Pontryagin's Maximum Principle is exhibited. Finally, applications to decomposition of optimal ...

Some Properties of Certain Subclasses of Close-to-Convex and Quasi-convex Functions with Respect to 2k-Symmetric Conjugate Points

some properties of certain subclasses of close-to-convex and quasi-convex functions with respect to 2k-symmetric conjugate points

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Starlike and Convex Functions with Respect to Conjugate Points

An analytic functions f(z) defined on 4 = {z : |z| < 1} and normalized by f(0) = 0, f ′(0) = 1 is starlike with respect to conjugate points