Abstract
The P-algorithm is an adaptive algorithm for approximating the global minimum of a continuous function on an interval, motivated by viewing the function as a sample path of a Gaussian process. In this paper we analyze the convergence of the P-algorithm for arbitrary continuous functions, as well as under the assumption of Wiener measure on the objective functions. In both cases the convergence rate is described in terms of a parameter of the algorithm and a functional of the objective function.
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Calvin, J.M. (2000). Convergence Rate of the P-Algorithm for Optimization of Continuous Functions. In: Pardalos, P.M. (eds) Approximation and Complexity in Numerical Optimization. Nonconvex Optimization and Its Applications, vol 42. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3145-3_8
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DOI: https://doi.org/10.1007/978-1-4757-3145-3_8
Publisher Name: Springer, Boston, MA
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