Stochastic optimization problems with nondifferentiable cost functionals
نویسندگان
چکیده
منابع مشابه
On Nondifferentiable and Nonconvex Vector Optimization Problems
In this paper, we prove the equivalence among the Minty vector variational-like inequality, Stampacchia vector variational-like inequality, and a nondifferentiable and nonconvex vector optimization problem. By using a fixed-point theorem, we establish also an existence theorem for generalized weakly efficient solutions to the vector optimization problem for nondifferentiable and nonconvex funct...
متن کاملImpossibility Results for Nondifferentiable Functionals∗
We examine challenges to estimation and inference when the objects of interest are nondifferentiable functionals of the underlying data distribution. This situation arises in a number of applications of bounds analysis and moment inequality models, and in recent work on estimating optimal dynamic treatment regimes. Drawing on earlier work relating differentiability to the existence of unbiased ...
متن کاملNondifferentiable Multiplier Rules for Optimization and Bilevel Optimization Problems
In this paper we study optimization problems with equality and inequality constraints on a Banach space where the objective function and the binding constraints are either differentiable at the optimal solution or Lipschitz near the optimal solution. Necessary and sufficient optimality conditions and constraint qualifications in terms of the Michel–Penot subdifferential are given, and the resul...
متن کاملConvergence of simultaneous perturbation stochastic approximation for nondifferentiable optimization
In this paper, we consider Simultaneous Perturbation Stochastic Approximation (SPSA) for function minimization. The standard assumption for convergence is that the function be three times differentiable, although weaker assumptions have been used for special cases. However, all work that we are aware of at least requires differentiability. In this paper, we relax the differentiability requireme...
متن کاملSampling and Cost-Sharing: Approximation Algorithms for Stochastic Optimization Problems
We consider twoand multistage versions of stochastic combinatorial optimization problems with recourse: in this framework, the instance for the combinatorial optimization problem is drawn from a known probability distribution π and is only revealed to the algorithm over two (or multiple) stages. At each stage, on receiving some more information about the instance, the algorithm is allowed to bu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Optimization Theory and Applications
سال: 1973
ISSN: 0022-3239,1573-2878
DOI: 10.1007/bf00934819