http://busoniu.net/teaching/to_optimisticoptimization_handout.pdf Web(2) A second algorithm, Simultaneous Optimistic Optimization (SOO), that does not require the knowledge of ‘. We show that SOO performs almost as well as DOO optimally-fitted. 2 Assumptions about the hierarchical partition and the function Our optimization algorithms will be implemented by resorting to a hierarchical partitioning of the

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WebHierarchical Optimistic Optimization (HOO) algorithm for solving the result-ing mathematical models. Machine learning methods and, in particular, bandit learning have already been used in portfolio optimization [14]. However, this is the first time that a machine learning approach, and in particular HOO, is WebHierarchical Optimistic Optimization with appropriate pa-rameters. As a consequence, we obtain theoretical regret bounds on sample efciency of our solution that depend on key problem parameters like smoothness, near-optimality dimension, and batch size. cumberland mountain mental health clinic

Optimistic Optimization - Busoniu

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