This monograph deals with methods for stochastic or data-driven optimization. The overall goal of these methods is to minimize a certain parameter-dependent objective function that for any parameter value is an expectation of a noisy sample performance objective whose measurement can be made from a real system or a simulation device.
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This monograph deals with methods for stochastic or data-driven optimization. The overall goal of these methods is to minimize a certain parameter-dependent objective function that for any parameter value is an expectation of a noisy sample performance objective whose measurement can be made from a real system or a simulation device.
Read Less
Add this copy of Gradient-Based Algorithms for Zeroth-Order Optimization to cart. $110.26, new condition, Sold by Just one more Chapter rated 3.0 out of 5 stars, ships from Miramar, FL, UNITED STATES, published 2025 by Now Publishers.
