This is a blackbox function optimization toolkit that finds the global optimum of a function given a finite budget of noisy evaluations. The algorithm does not require the knowledge of the function's smoothness.
StoSOO, follows an optimistic strategy to iteratively construct upper confidence bounds over the hierarchical partitions of the function domain to decide which point to sample next. A finite-time analysis of StoSOO shows that it performs almost as well as the best specifically-tuned algorithms even though the local smoothness of the function is not known.
Download apps, toolboxes, and other File Exchange content using Add-On Explorer in MATLAB.