Theodore V. Theodosopoulos

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For a class of stochastic restart algorithms we address the effect of a nonzero level of randomization in maximizing the convergence rate for general energy landscapes. The resulting characterization of the optimal level of randomization is investigated computationally for random as well as para-metric families of rugged energy landscapes.
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