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A Proximal Stochastic Variance Reduced Zeroth-order Algorithm using Structured Finite-Differences
Minimizing finite sums of functions is a central problem in optimization, arising in numerous practical applications. Such problems are commonly addressed using first-order optimization methods. However, these procedures cannot be used in settings where gradient information is unavailable. Finite-di
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