Backtracking step-size strategies (also known as adaptive step-size or approximate line-search) that set the step-size based on a sufficient decrease condition are the standard way to set the step-size on gradient descent and quasi-Newton methods. However, these techniques are much less common for Frank-Wolfe-like algorithms. In this blog post I …
This blog post extends the convergence theory from the first part of these notes on the
Frank-Wolfe (FW) algorithm with convergence guarantees on the primal-dual gap which generalize
and strengthen the convergence guarantees obtained in the first part.