27 citations · 64 across the 17 of their papers we have counts for
12 papers · 1 filter
Inexact Zeroth-Order Nonsmooth and Nonconvex Stochastic Composite Optimization and Applications
Spyridon Pougkakiotis, Dionysis Kalogerias
In this paper we present an inexact zeroth-order method suitable for the solution nonsmooth and nonconvex stochastic composite optimization problems, in which the objective is spli…
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…
An active-set method for sparse approximations. Part II: General piecewise-linear terms
Spyridon Pougkakiotis, Jacek Gondzio, Dionysios S. 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…
Strong Duality in Risk-Constrained Nonconvex Functional Programming
Dionysis Kalogerias, Spyridon Pougkakiotis
We show that a wide class of risk-constrained nonconvex functional optimization problems exhibit strong duality, regardless of nonconvexity. We develop two novel results under dist…
A Zeroth-order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization
Spyridon Pougkakiotis, Dionysios S. Kalogerias
In this paper we analyze a zeroth-order proximal stochastic gradient method suitable for the minimization of weakly convex stochastic optimization problems. We consider nonsmooth a…
An active-set method for sparse approximations. Part I: Separable terms
Spyridon Pougkakiotis, Jacek Gondzio, Dionysios S. Kalogerias
In this paper we present an active-set method for the solution of -regularized convex quadratic optimization problems. It is derived by combining a proximal method of multi…
General-purpose preconditioning for regularized interior point methods
Jacek Gondzio, Spyridon Pougkakiotis, John W. Pearson
In this paper we present general-purpose preconditioners for regularized augmented systems arising from optimization problems, and their corresponding normal equations. We discuss…
Sparse Approximations with Interior Point Methods
Valentina De Simone, Daniela di Serafino, Jacek Gondzio +2
Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods a…
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…
Fast Solution Methods for Convex Quadratic Optimization of Fractional Differential Equations
Spyridon Pougkakiotis, John W. Pearson, Santolo Leveque +1
In this paper, we present numerical methods suitable for solving convex quadratic Fractional Differential Equation (FDE) constrained optimization problems, with box constraints on…
An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programming
Spyridon Pougkakiotis, Jacek Gondzio
In this paper we combine an infeasible Interior Point Method (IPM) with the Proximal Method of Multipliers (PMM). The resulting algorithm (IP-PMM) is interpreted as a primal-dual r…
Dynamic Non-Diagonal Regularization in Interior Point Methods for Linear and Convex Quadratic Programming
Spyridon Pougkakiotis, Jacek Gondzio
In this paper, we present a dynamic non-diagonal regularization for interior point methods. The non-diagonal aspect of this regularization is implicit, since all the off-diagonal e…