Linearly convergent away-step conditional gradient for non-strongly convex functions

  title={Linearly convergent away-step conditional gradient for non-strongly convex functions},
  author={Amir Beck and Shimrit Shtern},
  journal={Math. Program.},
We consider the problem of minimizing a function, which is the sum of a linear function and a composition of a strongly convex function with a linear transformation, over a compact polyhedral set. Jaggi and Lacoste-Julien [14] showed that the conditional gradient method with away steps employed on the aforementioned problem without the additional linear term has linear rate of convergence, depending on the so-called pyramidal width of the feasible set. We revisit this result and provide a… CONTINUE READING
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