12 citations · 12 across the 5 of their papers we have counts for
14 papers
An efficient active-set method with applications to sparse approximations and risk minimization
Spyridon Pougkakiotis, Jacek Gondzio, Dionysis Kalogerias
In this paper we present an efficient active-set method for the solution of convex quadratic programming problems with general piecewise-linear terms in the objective, with applica…
Polynomial worst-case iteration complexity of quasi-Newton primal-dual interior point algorithms for linear programming
Jacek Gondzio, Francisco N. C. Sobral
Quasi-Newton methods are well known techniques for large-scale numerical optimization. They use an approximation of the Hessian in optimization problems or the Jacobian in system o…
Proximal stabilized Interior Point Methods for quadratic programming and low-frequency-updates preconditioning techniques
Stefano Cipolla, Jacek Gondzio
In this work, in the context of Linear and Quadratic Programming, we interpret Primal Dual Regularized Interior Point Methods (PDR-IPMs) in the framework of the Proximal Point Meth…
Random multi-block ADMM: an ALM based view for the QP case
Stefano Cipolla, Jacek Gondzio
Embedding randomization procedures in the Alternating Direction Method of Multipliers (ADMM) has recently attracted an increasing amount of interest as a remedy to the fact that th…
An Interior Point-Proximal Method of Multipliers for Positive Semi-Definite Programming
Spyridon Pougkakiotis, Jacek Gondzio
In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in [An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programmi…
A New Preconditioning Approach for an Interior Point-Proximal Method of Multipliers for Linear and Convex Quadratic Programming
Luca Bergamaschi, Jacek Gondzio, Ángeles Martínez +2
In this paper, we address the efficient numerical solution of linear and quadratic programming problems, often of large scale. With this aim, we devise an infeasible interior point…