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This paper presents regret-based adaptive search algorithms for non-stationary simulation-based discrete optimization problems.
Abstract—This paper presents regret-based adaptive search algorithms for non-stationary simulation-based discrete op- timization problems.
This paper presents regret-based adaptive search algorithms for non-stationary simulation-based discrete optimization problems with performance gains in ...
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We consider a non-stationary variant of a sequential stochastic optimization problem, in which the underlying cost functions may change along the horizon.
This paper considers simulation-based optimization of the performance of a regime switching stochastic system over a finite set of feasible alternatives.
Sep 14, 2015 · We consider a non-stationary variant of a sequential stochastic optimization problem, in which the underlying cost functions may change along the horizon.
A regret-based approach to non-stationary discrete stochastic optimization ... Best-response search algorithms for non-stationary discrete stochastic optimization.
Oct 11, 2022 · In this paper we study the non-stationary stochastic optimization question with bandit feedback and dynamic regret measures.
The rate of growth of the minimax regret in the stationary and non- function, Agarwal et al. (2013) showed that the minimax stationary settings under different ...
To achieve no (local) regret in this setting, we develop a prox-grad method based on stochastic first-order feedback, and a simpler method for when access to a ...