Add to ORKGThis paper describes two algorithms for the problem of minimizing a linear function over the intersection of an affine set and a convex set which is required to be the closure of the domain of a strongly self-concordant barrier function. One algorithm is a path-following method, while the other is a primal potential-reduction method. We give bounds on the number of iterations necessary to attain a given accuracy
International audienceSelf-concordant barriers are essential for interior-point algorithms in conic ...
We consider an interior point algorithm for convex programming in which the steps are generated by u...
We present the technical details of an interior--point method for the solution of subproblems that a...
Written for specialists working in optimization, mathematical programming, or control theory. The ge...
AbstractWe introduce two interior point algorithms for minimizing a convex function subject to linea...
We provide a survey of interior-point methods for linear programming and its extensions that are bas...
The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for li...
The purpose of this paper is to provide improved complexity results for several classes of structure...
In this paper we continue the development of a theoretical foundation for efficient primal-dual inte...
We present a framework for designing and analyzing primal-dual interior-point methods for convex opt...
We consider the Riemannian geometry defined on a convex set by the Hessian of a self-concordant barr...
Abstract. Many scientific and engineering applications feature nonsmooth convex minimization problem...
Besides the simplex algorithm, linear programs can also be solved via interior point methods. The th...
This study examines two different barrier functions and their use in both path-following and potenti...
Optimization is an important field of applied mathematics with many applications in various domains,...
International audienceSelf-concordant barriers are essential for interior-point algorithms in conic ...
We consider an interior point algorithm for convex programming in which the steps are generated by u...
We present the technical details of an interior--point method for the solution of subproblems that a...
Written for specialists working in optimization, mathematical programming, or control theory. The ge...
AbstractWe introduce two interior point algorithms for minimizing a convex function subject to linea...
We provide a survey of interior-point methods for linear programming and its extensions that are bas...
The modern era of interior-point methods dates to 1984, when Karmarkar proposed his algorithm for li...
The purpose of this paper is to provide improved complexity results for several classes of structure...
In this paper we continue the development of a theoretical foundation for efficient primal-dual inte...
We present a framework for designing and analyzing primal-dual interior-point methods for convex opt...
We consider the Riemannian geometry defined on a convex set by the Hessian of a self-concordant barr...
Abstract. Many scientific and engineering applications feature nonsmooth convex minimization problem...
Besides the simplex algorithm, linear programs can also be solved via interior point methods. The th...
This study examines two different barrier functions and their use in both path-following and potenti...
Optimization is an important field of applied mathematics with many applications in various domains,...
International audienceSelf-concordant barriers are essential for interior-point algorithms in conic ...
We consider an interior point algorithm for convex programming in which the steps are generated by u...
We present the technical details of an interior--point method for the solution of subproblems that a...