Add to ORKGWe formulate and prove a convex duality theorem for Bregman distances and present a technique based on auxiliary functions for deriving and proving convergence of iterative algorithms to minimize Bregman distance subject to linear constraints
This short article analyzes an interesting property of the Bregman iterative procedure for minimizin...
Se desarrolla una generalizaci\uf3n del m\ue9todo de punto proximal cl\ue1sico y el m\ue9todo de pun...
A broad class of optimization algorithms based on Bregman distances in Banach spaces is unified arou...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
summary:Integral functionals based on convex normal integrands are minimized subject to finitely man...
AbstractIn 2001, Della Pietra, Della Pietra, and Lafferty suggested a dual characterization of the B...
Given two point to set operators, one of which is maximally monotone, we introduce a new distance in...
The aim of this paper is twofold. First, several basic mathematical concepts involved in the constru...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
We consider methods for minimizing a convex function f that generate a sequence fx k g by taking ...
This short article analyzes an interesting property of the Bregman iterative procedure for minimizin...
Se desarrolla una generalizaci\uf3n del m\ue9todo de punto proximal cl\ue1sico y el m\ue9todo de pun...
A broad class of optimization algorithms based on Bregman distances in Banach spaces is unified arou...
We formulate and prove a convex duality theorem for Bregman distances and present a technique based ...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
In this article, we consider the proximal point method with Bregman distance applied to linear progr...
summary:Integral functionals based on convex normal integrands are minimized subject to finitely man...
AbstractIn 2001, Della Pietra, Della Pietra, and Lafferty suggested a dual characterization of the B...
Given two point to set operators, one of which is maximally monotone, we introduce a new distance in...
The aim of this paper is twofold. First, several basic mathematical concepts involved in the constru...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
International audienceWe propose a unifying algorithm for non-smooth non-convex optimization. The al...
We consider methods for minimizing a convex function f that generate a sequence fx k g by taking ...
This short article analyzes an interesting property of the Bregman iterative procedure for minimizin...
Se desarrolla una generalizaci\uf3n del m\ue9todo de punto proximal cl\ue1sico y el m\ue9todo de pun...
A broad class of optimization algorithms based on Bregman distances in Banach spaces is unified arou...