Ben Recht • 12/2/2025

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This article is a detailed lecture transcript from a graduate machine learning class, diving into the technical applications of policy gradient methods. It explains the core mathematical derivation of an unbiased gradient estimator for optimizing expected values over parameterized distributions and demonstrates how this principle can be used to build heuristic solvers for various problems, including optimization over probability simplices.

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#Machine Learning #Reinforcement Learning #Gradient Estimation