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Continuous Projection Generalized Extra-Gradient Quasi-Newton Second-Order Method for Solving Saddle Point Problems

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Abstract

The paper presents a study of a method for solving saddle point problems for convex-concave smooth functions with Lipschitz partial gradients on a convex closed subset of a finite-dimensional Euclidean space. The convergence and exponential convergence rate of the method are proved using convex analysis.

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REFERENCES

  1. K. Arrow, L. Hurwicz, and H. Uzawa, Studies in Nonlinear Programming (Stanford Univ. Press, Stanford, 1958).

    MATH  Google Scholar 

  2. G. M. Korpelevich, “Extrapolation gradient methods and their relation to augmented Lagrangian functions,” Ekon. Mat. Metody 19 (4), 694–703 (1983).

    MathSciNet  MATH  Google Scholar 

  3. A. S. Antipin, Gradient and Extragradient Approaches in Bilinear and Equilibrium Programming (Vychisl. Tsentr Ross. Akad. Nauk, Moscow, 2002) [in Russian].

    Google Scholar 

  4. A. S. Antipin and F. P. Vasil’ev, “On a continuous minimization method in spaces with a variable metric,” Russ. Math. 39 (12), 1–6 (1995).

    MathSciNet  MATH  Google Scholar 

  5. V. G. Malinov, “On projection generalized two-step two-stage quasi-Newton minimization method and optimization of the trajectory of aircraft,” Zh. Srednevolzh. Mat. O–va 12 (4), 37–48 (2010).

    MATH  Google Scholar 

  6. V. G. Malinov, “A second-order continuous projection minimization method with a variable metric,” Zh. Srednevolzh. Mat. O–va 16 (1), 121–134 (2014).

    Google Scholar 

  7. V. G. Malinov, “A generalized extragradient quasi-Newton method for solving saddle point and other problems,” Proceedings of the 9th Moscow International Conference on Operations Research (ORM2018), Moscow, October 22–27, 2018 (MAKS, Moscow, 2018), Vol. 2, pp. 124–126.

  8. F. P. Vasil’ev, Numerical Methods for Optimization Problems (Nauka, Moscow, 1988) [in Russian].

    Google Scholar 

  9. V. G. Karmanov, Mathematical Programming (Nauka, Moscow, 1975) [in Russian].

    MATH  Google Scholar 

  10. A. S. Antipin and Z. S. Khamraeva, Second-Order Controlled Saddle Differential Gradient Methods (Vychisl. Tsentr Ross. Akad. Nauk, Moscow, 1996) [in Russian].

    Google Scholar 

  11. A. S. Antipin, “Second-order controlled differential gradient methods for solving equilibrium problems,” Differ. Equations 35 (5), 592–601 (1999).

    MathSciNet  MATH  Google Scholar 

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Correspondence to V. G. Malinov.

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Translated by E. Chernokozhin

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Malinov, V.G. Continuous Projection Generalized Extra-Gradient Quasi-Newton Second-Order Method for Solving Saddle Point Problems. Comput. Math. and Math. Phys. 62, 753–765 (2022). https://doi.org/10.1134/S0965542522050086

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  • DOI: https://doi.org/10.1134/S0965542522050086

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