Smoothing and Worst-Case Complexity for Direct-Search Methods in Nonsmooth Optimization

@inproceedings{Garmanjani2012SmoothingAW,
  title={Smoothing and Worst-Case Complexity for Direct-Search Methods in Nonsmooth Optimization},
  author={R. Garmanjani and Lu{\'i}s Nunes Vicente},
  year={2012}
}
In the context of the derivative-free optimization of a smooth objective function, it has been shown that the worst case complexity of direct-search methods is of the same order as the one of steepest descent for derivative-based optimization, more precisely that the number of iterations needed to reduce the norm of the gradient of the objective function below a certain threshold is proportional to the inverse of the threshold squared. Motivated by the lack of such a result in the non-smooth… CONTINUE READING