Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
×
Mar 28, 2023 · We proceed with analyzing convergence rates for the multiplier estimates, which for the quadratic penalty are given by (1.7). We shall consider ...
CONVERGENCE RATE ESTIMATES. FOR PENALTY METHODS REVISITED. A.F. Izmailov1 and M.V. Solodov2. September 25, 2022 (revised March 9, 2023). ABSTRACT.
Moreover, using solutions of the penalty subproblem, one can obtain certain useful Lagrange multipliers estimates whose distance to the optimal ones is also at ...
Moreover, using solutions of the penalty subproblem, one can obtain certain useful Lagrange multipliers estimates whose distance to the optimal ones is also at ...
This paper proposes a linearized quadratic penalty method that linearizes the objective function and the functional constraints in the penalty formulation ...
Title. Convergence rate estimates for penalty methods revisited. Authors. Izmailov, A. F.; Solodov, M. V.. Abstract. For the classical quadratic penalty, ...
Convergence rate estimates for penalty methods revisited. A. Izmailov, and M. Solodov. Comput. Optim. Appl., 85 (3): 973-992 (July 2023 ). 1. 1. Meta data.
People also ask
A very simple and efficient approach to deriving estimates of the convergence rate for the penalty methods is suggested. The approach is based on the ...
Convergence rate estimates for penalty methods revisited. Article 28 March 2023. Linear convergence of first order methods for non-strongly convex optimization.
Convergence rate estimates for penalty methods revisited. Computational Optimization and Applications, Vol. 85, No. 3 | 28 March 2023. Convergence of ...