My search problem is essentially sphere with a noisy evaluation. This noise is causing CMA-ES to converge at a ridiculously slow rate. Is there any way to force CMA-ES to converge in an approximate manner in the face of noise?

Note: I don't need convergence to the exact optimum as I can fine tune that later, so I'm looking for a fast convergence to the near optimum (in a unimodal, but noisy search space).

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