Stochastic Optimization

Uncertainty Modeling

Probability Distributions

Scenario-Based Approaches

Expected Value Problems

Here-and-Now vs Wait-and-See Decisions

Recourse Functions

L-Shaped Method

Benders Decomposition

Decision Trees

Scenario Trees

Non-Anticipativity Constraints

Progressive Hedging Algorithm

Individual Chance Constraints

Joint Chance Constraints

Probabilistic Programming

Sample Average Approximation

Uncertainty Sets

Robust Counterpart Formulation

Adjustable Robust Optimization

Distributionally Robust Optimization

Robbins-Monro Algorithm

Stochastic Gradient Methods

Convergence Analysis

Applications to Machine Learning