HAL (France)
open access
Global optimization by random perturbation of the gradient method with a fixed parameter
The paper deals with the global minimization of a differentiable cost function mapping a ball of a finite dimensional Euclidean space into an interval of real numbers. It is established that a suitable random perturbation of the gradient method with a fixed parameter generates a bounded minimizing s
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