Spyridon Pougkakiotis

According to our database, Spyridon Pougkakiotis authored at least 14 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Model-Free Learning of Two-Stage Beamformers for Passive IRS-Aided Network Design.

Hassaan Hashmi, Spyridon Pougkakiotis, Dionysis Kalogerias

IEEE Trans. Signal Process., 2024

Strong Duality Relations in Nonconvex Risk-Constrained Learning.

Dionysis Kalogerias, Spyridon Pougkakiotis

Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

2023

A Zeroth-Order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization.

Spyridon Pougkakiotis, Dionysis Kalogerias

SIAM J. Sci. Comput., October, 2023

Model-Free Learning of Optimal Two-Stage Beamformers for Passive IRS-Aided Network Design.

Hassaan Hashmi, Spyridon Pougkakiotis, Dionysios S. Kalogerias

CoRR, 2023

Model-Free Learning of Optimal Beamformers for Passive IRS-Assisted Sumrate Maximization.

Hassaan Hashmi, Spyridon Pougkakiotis, Dionysios S. Kalogerias

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Sparse Approximations with Interior Point Methods.

Valentina De Simone, Daniela di Serafino, Jacek Gondzio, Spyridon Pougkakiotis, Marco Viola

SIAM Rev., 2022

An Interior Point-Proximal Method of Multipliers for Linear Positive Semi-Definite Programming.

Spyridon Pougkakiotis, Jacek Gondzio

J. Optim. Theory Appl., 2022

A semismooth Newton-proximal method of multipliers for 𝓁₁-regularized convex quadratic programming.

Spyridon Pougkakiotis, Jacek Gondzio

CoRR, 2022

General-purpose preconditioning for regularized interior point methods.

Jacek Gondzio, Spyridon Pougkakiotis, John W. Pearson

Comput. Optim. Appl., 2022

2021

A new preconditioning approach for an interior point-proximal method of multipliers for linear and convex quadratic programming.

Luca Bergamaschi, Jacek Gondzio, Ángeles Martínez, John W. Pearson, Spyridon Pougkakiotis

Numer. Linear Algebra Appl., 2021

An interior point-proximal method of multipliers for convex quadratic programming.

Spyridon Pougkakiotis, Jacek Gondzio

Comput. Optim. Appl., 2021

2020

Fast Solution Methods for Convex Quadratic Optimization of Fractional Differential Equations.

Spyridon Pougkakiotis, John W. Pearson, Santolo Leveque, Jacek Gondzio

SIAM J. Matrix Anal. Appl., 2020

2019

Dynamic Non-diagonal Regularization in Interior Point Methods for Linear and Convex Quadratic Programming.

Spyridon Pougkakiotis, Jacek Gondzio

J. Optim. Theory Appl., 2019

2016

Efficient KLMS and KRLS algorithms: A random fourier feature perspective.

Pantelis Bouboulis, Spyridon Pougkakiotis, Sergios Theodoridis

Proceedings of the IEEE Statistical Signal Processing Workshop, 2016