Random search is an optimization technique used to find the best solution to a problem by randomly sampling points in the search space. This method does not rely on any specific gradient information and instead explores various combinations of parameters, making it particularly useful for high-dimensional and complex optimization problems, such as those encountered in neural networks.
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