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On quasi-convex smooth optimization problems by a comparison oracle
A. V. Gasnikov, M. S. Alkousa, A. V. Lobanov +4
Frequently, when dealing with many machine learning models, optimization problems appear to be challenging due to a limited understanding of the constructions and characterizations…
Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems
O. S. Savchuk, M. S. Alkousa, A. S. Shushko +4
In this paper, we propose some accelerated methods for solving optimization problems under the condition of relatively smooth and relatively Lipschitz continuous functions with an…
Universal methods for variational inequalities: deterministic and stochastic cases
Anton Klimza, Alexander Gasnikov, Fedor Stonyakin +1
In this paper, we propose universal proximal mirror methods to solve the variational inequality problem with Holder continuous operators in both deterministic and stochastic settin…
Higher Degree Inexact Model for Optimization problems
Mohammad Alkousa, Fedor Stonyakin, Alexander Gasnikov +2
In this paper, it was proposed a new concept of the inexact higher degree -model of a function that is a generalization of the inexact -model, -oracle an…