Frank-Wolfe Algorithm

The Frank-Wolfe Algorithm is an optimization method used to find the best solution within certain constraints. Imagine trying to minimize a function, like cost or error, while ensuring your solution stays within a specific set, such as a shape or region. The algorithm starts at an initial point, then repeatedly moves toward the direction that most reduces the function, choosing steps along the edges or corners of the feasible region. This process continues until it converges to an optimal or near-optimal solution, making it efficient for large-scale problems with complex constraints.