A noisy gradient descent with adaptive Gaussian noise converges linearly to the global minimizer of nearly convex functions when a sharp lower bound is known.
Recursive stochastic algorithms for global optimization in Rd
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A Stochastic Gradient Descent Method for Globally Minimizing Nearly Convex Functions
A noisy gradient descent with adaptive Gaussian noise converges linearly to the global minimizer of nearly convex functions when a sharp lower bound is known.