# Complexity bounds for primal-dual methods minimizing the model of objective function

@article{Nesterov2018ComplexityBF,
title={Complexity bounds for primal-dual methods minimizing the model of objective function},
author={Y. Nesterov},
journal={Mathematical Programming},
year={2018},
volume={171},
pages={311-330}
}
• Y. Nesterov
• Published 2018
• Mathematics, Computer Science
• Mathematical Programming
We provide Frank–Wolfe ($$\equiv$$≡ Conditional Gradients) method with a convergence analysis allowing to approach a primal-dual solution of convex optimization problem with composite objective function. Additional properties of complementary part of the objective (strong convexity) significantly accelerate the scheme. We also justify a new variant of this method, which can be seen as a trust-region scheme applying to the linear model of objective function. For this variant, we prove also the… Expand

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