Abstract
We study convergence rates of $\mathbb{R}$-valued algorithms, especially in the case of multiple targets and simulated annealing. We precise, for example, the convergence rate of simulated annealing algorithms, whose weak convergence to a distribution concentrated on the potential's minima had been established by Gelfand and Mitter or by Hwang and Sheu.
Citation
Mariane Pelletier. "Weak convergence rates for stochastic approximation with application to multiple targets and simulated annealing." Ann. Appl. Probab. 8 (1) 10 - 44, February 1998. https://doi.org/10.1214/aoap/1027961032
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