Stochastic Gradient Optimization TechniquesNumerical methods in inverse problemsOptimization and Variational Analysis

I. Konnov

2026.1.1Russian Mathematics

DOI: 10.3103/s1066369x26700039

Abstract

We propose a class of dual gradient Uzawa type methods for general convex constrained optimization problems. In order to provide stable convergence we utilize the partial regularization in primal variables and additional constraints for dual variables. Convergence of the method is established under rather

Citation format

KONNOV, I. Dual gradient method with partial regularization for convex optimization problems. Russian Mathematics, 2026, 70(1): 21–33.