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

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  • Yurii Nesterov

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  • Yurii Nesterov, 2018. "Complexity bounds for primal-dual methods minimizing the model of objective function," LIDAM Reprints CORE 2992, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:2992
    Note: In : Mathematical Programming Series A, 171, 311-330, 2018
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    Cited by:

    1. Z. R. Gabidullina, 2019. "Adaptive Conditional Gradient Method," Journal of Optimization Theory and Applications, Springer, vol. 183(3), pages 1077-1098, December.
    2. Doikov, Nikita & Nesterov, Yurii, 2021. "Optimization Methods for Fully Composite Problems," LIDAM Discussion Papers CORE 2021001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Ya-Feng Liu & Xin Liu & Shiqian Ma, 2019. "On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 632-650, May.
    4. Doikov, Nikita & Nesterov, Yurii, 2020. "Affine-invariant contracting-point methods for Convex Optimization," LIDAM Discussion Papers CORE 2020029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Masoud Ahookhosh, 2019. "Accelerated first-order methods for large-scale convex optimization: nearly optimal complexity under strong convexity," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(3), pages 319-353, June.

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