frank wolfe algorithm

The Frank-Wolfe algorithm is an iterative optimization method for constrained convex problems. It minimizes a convex function over a convex set by linearizing the objective at each step, solving a linear subproblem to find a feasible direction, and updating the solution via a convex combination. Ideal for large-scale problems with simple constraints, it’s efficient but may converge slowly for complex objectives.