Convergence Rate of Frank Wolfe for Non Convex Objectives
We give a simple proof that the Frank Wolfe algorithm obtains a stationary point at a rate of $O(1/\sqrt{t} on non convex objectives with a Lipschitz continuous gradient. Our analysis is affine invariant and is the first, to the best of our knowledge, giving a similar rate to what was already proven for projected gradient methods (though on slightly different measures of stationarity)
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