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Convex Sets and FunctionsIntroduces convex sets and functions, discussing minimizers, optimality conditions, and characterizations, along with examples and key inequalities.
Jensen's InequalityCovers Jensen's inequality, stating that the convex function of the average is less than or equal to the average of the function.
Box-Cox TransformExplores the Box-Cox transform for investigating nonlinear specifications in models using a parameter lambda.
Convexity and JacobiansExplores convexity, Jacobians, subdifferentials, and convergence rates in optimization and function analysis.
Optimization BasicsIntroduces optimization basics, covering logistic regression, derivatives, convex functions, gradient descent, and second-order methods.