Convex optimization use programming

  • How is convex optimization used?

    Convex optimization has become an essential tool in machine learning because many real-world problems can be modeled as convex optimization problems.
    For example, in classification problems, the goal is to find the best hyperplane that separates the data points into different classes..

  • Some real-life examples of convex optimization problems include the following: Scheduling of flights: Flight scheduling is an example convex optimization problem.
    It involves finding flight times that minimize costs like fuel, pilot/crew costs, etc. while maximizing the number of passengers.Apr 23, 2023
A convex optimization problem is a problem where all of the constraints are convex functions, and the objective is a convex function if minimizing, or a concave function if maximizing. Linear functions are convex, so linear programming problems are convex problems.
A convex optimization problem is a problem where all of the constraints are convex functions, and the objective is a convex function if minimizing, or a concave function if maximizing. Linear functions are convex, so linear programming problems are convex problems.

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