Self-adaptive proximal algorithms for equilibrium problems in Hadamard space

Authors

  • Vladimir V. Semenov Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv https://orcid.org/0000-0002-3280-8245
  • Vladislava Chernorai Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
  • Serhii Denysov

DOI:

https://doi.org/10.31713/MCIT.2025.081

Keywords:

Hadamard space, equilibrium problem, algorithms, convergence

Abstract

We consider a new self-adaptive algorithms for equilibrium problem in Hadamard spaces. At each step of the algorithms, the sequential minimization of two special strongly convex functions is performed. Our self-adaptive algorithms do not calculate bifunction values at additional points and do not require knowledge of bifunctions' Lipschitz constants. For pseudomonotone bifunctions of Lipschitz-type, theorems on weak convergence of sequences generated by algorithms are proved.

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Published

2025-11-06

How to Cite

Semenov, V. V., Chernorai, V., & Denysov, S. (2025). Self-adaptive proximal algorithms for equilibrium problems in Hadamard space. Modeling, Control and Information Technologies, (8), 264–266. https://doi.org/10.31713/MCIT.2025.081

Issue

No. 8 (2025): Modeling, control and information technologies

Section

Mathematical, computer modeling and computational methods

License

Copyright (c) 2025 Modeling, Control and Information Technologies: Proceedings of International scientific and practical conference

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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