Convex Sets: MGT-418 LectureOn Convex Optimization covers course organization, mathematical optimization problems, solution concepts, and optimization methods.
Convex OptimizationCovers an overview of convex optimization, affine sets, polyhedra, ellipsoids, and convex functions.
Mixture models: summarySummarizes mixtures of logit models, covering various mixing methods and modeling techniques for taste heterogeneity.
Bezier Curves IICovers Bezier curves, de Casteljau Algorithm, properties, derivatives, splines, and end-points.
Mixtures: introductionIntroduces mixtures, covers discrete and continuous mixtures, explores examples, and discusses combining probit and logit models.
Linear Programming BasicsCovers the basics of linear programming, defining corners, extreme points, and feasible solutions within polyhedrons.
