Yedidya Kfir

EvoGrad: Evolutionary-Weighted Gradient and Hessian Learning for Black-Box Optimization

Black-box algorithms aim to optimize functions without access to their analytical structure or gradient information, making them essential when gradients are unavailable or computationally expensive to obtain. Traditional methods for black-box optimization (BBO) primarily utilize non-parametric mode