Add to ORKGIn this article, we consider the proximal point method with Bregman distance applied to linear programming problems, and study the dual sequence obtained from the optimal multipliers of the linear constraints of each subproblem. We establish the convergence of this dual sequence, as well as convergence rate results for the primal sequence, for a suitable family of Bregman distances. These results are obtained by studying first the limiting behavior of a certain perturbed dual path and then the behavior of the dual and primal paths. 1
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...
A generalization of the classical proximal point method and the method of proximal point with Bregma...
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
Proximal methods are an important class of algorithms for solving nonsmooth, constrained, large-scal...
Proximal methods are an important class of algorithms for solving nonsmooth, constrained, large-scal...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
In this article, we develop a generalized proximal point algorithm for finding a weak Pareto optimal...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
AbstractStrassen's result on the Prokhorov's distance is proved by means of linear programming techn...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
© 2017 Springer Science+Business Media, LLC The proximal point algorithm (PPA) has been well studie...
We consider methods for minimizing a convex function f that generate a sequence fx k g by taking ...
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...
A generalization of the classical proximal point method and the method of proximal point with Bregma...
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
Proximal methods are an important class of algorithms for solving nonsmooth, constrained, large-scal...
Proximal methods are an important class of algorithms for solving nonsmooth, constrained, large-scal...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
In this article, we develop a generalized proximal point algorithm for finding a weak Pareto optimal...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
AbstractStrassen's result on the Prokhorov's distance is proved by means of linear programming techn...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
Proximal distance algorithms combine the classical penalty method of constrained minimization with d...
© 2017 Springer Science+Business Media, LLC The proximal point algorithm (PPA) has been well studie...
We consider methods for minimizing a convex function f that generate a sequence fx k g by taking ...
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...
A generalization of the classical proximal point method and the method of proximal point with Bregma...
This paper establishes convergence of generalized Bregman-function-based proximal point algorithms w...