Fast adaptive by constants of strong-convexity and Lipschitz for gradient first order methods

@article{Pletnev2020FastAB,
  title={Fast adaptive by constants of strong-convexity and Lipschitz for gradient first order methods},
  author={Nikita Pletnev},
  journal={Computer Research and Modeling},
  year={2020}
}
  • N. Pletnev
  • Published 8 September 2020
  • Computer Science
  • Computer Research and Modeling
The work is devoted to the construction of efficient and applicable to real tasks first-order methods of convex optimization, that is, using only values of the target function and its derivatives. Construction uses OGM-G, fast gradient method which is optimal by complexity, but requires to know the Lipschitz constant for gradient and the strong convexity constant to determine the number of steps and step length. This requirement makes practical usage impossible. An adaptive on the constant for… 

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