27 citations · 64 across the 17 of their papers we have counts for
19 papers
Data-Driven Two-Stage IRS-Aided Sumrate Maximization with Inexact Precoding
Hassaan Hashmi, Spyridon Pougkakiotis, Dionysis Kalogerias
We propose iZoSGA, a data-driven learning algorithm for joint passive long-term intelligent reflective surface (IRS)-aided beamforming and active short-term precoding in wireless n…
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…
Data-Driven Learning of Two-Stage Beamformers in Passive IRS-Assisted Systems with Inexact Oracles
Spyridon Pougkakiotis, Hassaan Hashmi, Dionysis Kalogerias
We develop an efficient data-driven and model-free unsupervised learning algorithm for achieving fully passive intelligent reflective surface (IRS)-assisted optimal short/long-term…
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…
Strong Duality Relations in Nonconvex Risk-Constrained Learning
Dionysis Kalogerias, Spyridon Pougkakiotis
We establish strong duality relations for functional two-step compositional risk-constrained learning problems with multiple nonconvex loss functions and/or learning constraints, r…
Model-Free Learning of Two-Stage Beamformers for Passive IRS-Aided Network Design
Hassaan Hashmi, Spyridon Pougkakiotis, Dionysios S. Kalogerias
Electronically tunable metasurfaces, or Intelligent Reflective Surfaces (IRSs), are a popular technology for achieving high spectral efficiency in modern wireless systems by shapin…
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…
Model-Free Learning of Optimal Beamformers for Passive IRS-Assisted Sumrate Maximization
Hassaan Hashmi, Spyridon Pougkakiotis, Dionysios S. Kalogerias
Although Intelligent Reflective Surfaces (IRSs) are a cost-effective technology promising high spectral efficiency in future wireless networks, obtaining optimal IRS beamformers is…
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…
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…
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…
Efficient KLMS and KRLS Algorithms: A Random Fourier Feature Perspective
Pantelis Bouboulis, Spyridon Pougkakiotis, Sergios Theodoridis
We present a new framework for online Least Squares algorithms for nonlinear modeling in RKH spaces (RKHS). Instead of implicitly mapping the data to a RKHS (e.g., kernel trick), w…