An Adaptive Univariate Global Optimization Algorithm and Its Convergence Rate under the Wiener Measure

We describe an adaptive algorithm for approximating the global minimum of a continuous univariate function. The convergence rate of the error is studied for the case of a random objective function distributed according to the Wiener measure.