Optimization, Machine Learning, Convex Optimization, Data Science, Data Analytics.
figure above, X is the set of all feasible points of a function. Geometrically, the optimal point x lies in the boundary of the feasible set. The gradient at point x will form a supporting hyperplane for the feasible points. This is because we know from Chapter 3 here, we know that supporting