Convex optimization

programming method to achieve the best outcome in a mathematical model

set of methods for supervised statistical learning

gradient descent method used for the minimization of an objective function

subfield of mathematical optimization

term in mathematical optimization theory

right|thumb|A convex function (blue) and "subtangent lines" at x_0 (red). In mathematics, the subderivative (or subgradient) generalizes the derivative to convex functions which are not necessarily differentiable. The set of subderivatives at a point is called the subdifferential at that point. Subderivatives arise in convex analysis, the study of convex functions, often in connection to convex optimization.

function for which every set of inputs whose value is below a given threshold is convex

subfield of convex optimization

result in convex geometry

optimization problem subject to posynomial constraints

iterative method for minimizing convex functions

Measure of investment risk

concept in convex optimization

functions used to evaluate optimization algorithms

continuous function whose value increases to infinity

significant topic in economics

condition in mathematical optimization

Concept in optimization

concept in convex optimization mathematics

subfield of convex optimization

mathematical convex optimization

convex optimization problem

economics