9 papers
Fourier Symmetrization for Geometric Quantum Machine Learning
Letao Wang, Abdel Lisser, Sreejith Sreekumar +1
Geometric quantum machine learning incorporates symmetry into quantum models, but how symmetry shapes their expressivity and guides effective model design remains insufficiently un…
Distributionally Robust Linearly Constrained Minimum Variance Beamforming Under Steering-Vector Mismatch
Raneem Madani, Abdel Lisser, Zeno Toffano
Linearly constrained minimum variance (LCMV) beamforming is a fundamental technique for controlling the array response toward multiple desired signals while suppressing interferenc…
Distributionally Robust Complex Chance-Constrained Optimization
Raneem Madani, Abdel Lisser, Zeno Toffano
This paper introduces a framework for Chance-Constrained Optimization with Complex Variables, addressing complex linear programming for both individual and joint probabilistic cons…
Robust Chance Constrained Complex Zero-Sum Games
Raneem Madani, Abdel Lisser, Zeno Toffano
This paper develops a unified framework for zero-sum games in which both the pure strategies and the payoff matrices contain complex-valued entries. By leveraging a linear isomorph…
A Complex-Valued Continuous-Variable Quantum Approximation Optimization Algorithm (CCV-QAOA)
Raneem Madani, Abdel Lisser, Zeno Toffano
Continuous-variable (CV) quantum systems offer a natural framework for continuous optimization through their infinite-dimensional Hilbert spaces. In this paper, we propose the Comp…
Distributionally Robust Geometric Joint Chance-Constrained Optimization: Neurodynamic Approaches
Ange Valli, Siham Tassouli, Abdel Lisser
This paper proposes a two-time scale neurodynamic duplex approach to solve distributionally robust geometric joint chance-constrained optimization problems. The probability distrib…
Decision-dependent distributionally robust standard quadratic optimization with Wasserstein ambiguity
Immanuel M. Bomze, Daniel de Vicente, Abdel Lisser +1
The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without assuming convexity or concavity of the quadratic form,…
Chance-Constrained Optimization with Complex Variables
Raneem Madani, Abdel Lisser
Optimization problems involving complex variables, when solved, are typically transformed into real variables, often at the expense of convergence rate and interpretability. This p…
Convexity of chance constraints for elliptical and skewed distributions with copula structures dependent on decision variables
Heng Zhang, Abdel Lisser
Chance constraints describe a set of given random inequalities depending on the decision vector satisfied with a large enough probability. They are widely used in decision making u…