Optimization
Computational Mathematics
Risk-aware Decision-making
Data Science, Operational Research and Engineering Applications
Inexact zeroth-order nonsmooth and nonconvex stochastic composite optimization and applications, Journal of Nonlinear and Variational Analysis, to appear (2025)
S. Pougkakiotis, D. Kalogerias
Data-driven learning of two-stage beamformers in passive IRS-assisted systems with inexact oracles, IEEE Access, 13 (2025)
S. Pougkakiotis, H. Hashmi, D. Kalogerias
An efficient active-set method with applications to sparse approximations and risk minimization, Journal of Scientific Computing, 104 (2025)
S. Pougkakiotis, J. Gondzio, D. Kalogerias
Model-free learning of two-stage beamformers for passive IRS-aided network design, IEEE Transactions on Signal Processing (2023)
H. Hashmi, S. Pougkakiotis, D. Kalogerias
A zeroth-order proximal stochastic gradient method for weakly convex stochastic optimization, SIAM Journal on Scientific Computing, 45 (2023)
S. Pougkakiotis, D. Kalogerias
General-purpose preoconditioning for regularized interior point methods, Computational Optimization and Applications, 83 (2022)
J. Gondzio, S. Pougkakiotis, J. W. Pearson
An interior point-proximal method of multipliers for linear positive semi-definite programming, Journal of Optimization Theory and Applications, 192 (2022)
S. Pougkakiotis, J. Gondzio
Sparse approximations with interior point methods, SIAM Review, 64(4) (2022)
V. De Simone, D. di Serafino, J. Gondzio, S. Pougkakiotis, M. Viola
A new preconditioning approach for an interior point‐proximal method of multipliers for linear and convex quadratic programming, Numerical Linear Algebra with Applications, 28(4) (2021)
L. Bergamaschi, J. Gondzio, Á. Martinez, J. W. Pearson, S. Pougkakiotis
An interior point-proximal method of multipliers for convex quadratic programming, Computational Optimization and Applications, 78 (2021)
S. Pougkakiotis, J. Gondzio
Fast solution methods for convex quadratic optimization of fractional differential equations, SIAM Journal on Matrix Analysis and Applications, 41(3) (2020)
S. Pougkakiotis, J. W. Pearson, S. Leveque, J. Gondzio
Dynamic non-diagonal regularization in interior point methods for linear and convex quadratic programming, Journal of Optimization Theory and Applications, 181 (2019)
S. Pougkakiotis, J. Gondzio
Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents, Advances in Neural Information Processing Systems (NeurIPS) (2025)
J. H. Lee, B. Saglam, S. Pougkakiotis, A. Karbasi, D. Kalogerias
Strong duality relations in nonconvex risk-constrained learning, 58th Annual Conference on Information Sciences and Systems (CISS) (2024)
D. Kalogerias, S. Pougkakiotis
Model-free learning of optimal beamformers for passive IRS-assisted sumrate maximization, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2023)
H. Hashmi, S. Pougkakiotis, D. Kalogerias
Efficient KLMS and KRLS algorithms: A random Fourier feature perspective, IEEE/SP Workshop on Statistical Signal Processing (SSP) (2016)
P. Bouboulis, S. Pougkakiotis, S. Theodoridis
Ultra-Reliable Risk-Aggregated Sum Rate Maximization via Model-Aided Deep Learning, arXiv preprint (2025)
H. Hashmi, S. Pougkakiotis, D. Kalogerias
Data-driven two-stage IRS-aided sumrate maximization with inexact precoding, arXiv preprint (2025)
H. Hashmi, S. Pougkakiotis, D. Kalogerias
Strong duality in risk-constrained nonconvex functional programming, arXiv preprint (2023)
D. Kalogerias, S. Pougkakiotis
An active-set method for sparse approximations. Part II: General piecewise-linear terms, arXiv preprint (2023)
S. Pougkakiotis, J. Gondzio, D. Kalogerias
An active-set method for sparse approximations. Part I: Separable ℓ1 terms, arXiv preprint (2023)
S. Pougkakiotis, J. Gondzio, D. Kalogerias
Regularized Interior Point Methods for Convex Programming, S. Pougkakiotis, PhD Thesis (2021)
Random Fourier Features: Theory and Applications, S. Pougkakiotis, BSc Thesis (2016)