We investigate projected scaled gradient (PSG) methods for convex minimization problems. These methods perform a descent step along a diagonally scaled gradient direction followed by a feasibility regaining step via orthogonal projection onto the constraint set. This constitutes a generalized algorithmic structure that encompasses as special cases the gradient projection method, the projected Newton method, the projected Landweber-type methods and the generalized expectation-maximization (EM)-type methods. We prove the convergence of the PSG methods in the presence of bounded perturbations. This resilience to bounded perturbations is relevant to the ability to apply the recently developed superiorization methodology to PSG methods, in parti...
Abstract-This paper considers some aspects of a gradient projection method proposed by Goldstein [l]...
We develop a general approach to convergence analysis of feasible descent methods in the presence of...
Abstract In this paper, we present a brief review on the central results of two generalizations of a...
The gradient projection algorithm plays an important role in solving constrained convex minimization...
The aim of this paper is to deepen the convergence analysis of the scaled gradient projection (SGP) ...
Abstract The convex feasibility problem (CFP) is at the core of the modeling of many problems in var...
A class of scaled gradient projection methods for optimization problems with simple constraints is c...
Abstract The proximal gradient algorithm is an appealing approach in finding solutions of non-smooth...
A class of scaled gradient projection methods for optimization problems with simple constraints is c...
A class of scaled gradient projection methods for optimization problems with simple constraints is ...
We consider the convex feasibility problem (CFP) in Hilbert space and concentrate on the study of st...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
Abstract-This paper considers some aspects of a gradient projection method proposed by Goldstein [l]...
We develop a general approach to convergence analysis of feasible descent methods in the presence of...
Abstract In this paper, we present a brief review on the central results of two generalizations of a...
The gradient projection algorithm plays an important role in solving constrained convex minimization...
The aim of this paper is to deepen the convergence analysis of the scaled gradient projection (SGP) ...
Abstract The convex feasibility problem (CFP) is at the core of the modeling of many problems in var...
A class of scaled gradient projection methods for optimization problems with simple constraints is c...
Abstract The proximal gradient algorithm is an appealing approach in finding solutions of non-smooth...
A class of scaled gradient projection methods for optimization problems with simple constraints is c...
A class of scaled gradient projection methods for optimization problems with simple constraints is ...
We consider the convex feasibility problem (CFP) in Hilbert space and concentrate on the study of st...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
© 2017 Informa UK Limited, trading as Taylor & Francis Group We suggest simple implementable modif...
Abstract-This paper considers some aspects of a gradient projection method proposed by Goldstein [l]...
We develop a general approach to convergence analysis of feasible descent methods in the presence of...
Abstract In this paper, we present a brief review on the central results of two generalizations of a...