Synopsis
1. Optimization. 2. Discrete-Event Processes. 3. Derivatives. 4. Simulation and Sensitivity Estimation. 5. Stochastic Approximation. A: Metric Spaces. B: Sequences and Series. C: Matrix Algebra. D: Derivatives. E: Convexity and Convex Projections. F: Set-Wise Convergence.G: Duality and Lagrangians. H: Probability Spaces and Random Variables. I: Convergence of Random Variables. J: The Wasserstein Distance. K: Conditional Expectations. L: Martingales. M: Choquet Theory. N: Coupling. Index.
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