Convergence Rate of Frank-Wolfe for Non-Convex Objectives

@article{LacosteJulien2016ConvergenceRO,
  title={Convergence Rate of Frank-Wolfe for Non-Convex Objectives},
  author={Simon Lacoste-Julien},
  journal={CoRR},
  year={2016},
  volume={abs/1607.00345}
}
We give a simple proof that the Frank-Wolfe algorithm obtains a stationary point at a rate of O(1/ √ 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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Introductory Lectures on Convex Optimization

  • Y. Nesterov
  • Kluwer Academic Publishers,
  • 2004
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