Abstract:

Frank-Wolfe algorithms are first-order methods that support structured convex constraints, over which linear optimization can be performed efficiently. We present FrankWolfe.jl, a library for flexible and high-performance Frank-Wolfe algorithms. In particular, we will detail design choices that allow warm starts, scaling to large problems and some use cases leveraging those features.