Panagiotis D. Grontas

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20242026

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math.OC2025

Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach

Colin Dirren, Mattia Bianchi, Panagiotis D. Grontas +2

We study the convex-concave bilinear saddle-point problem $min_{x} max_{y} f (x) + y^{⊤} A x - g (y)$ , where both, only one, or none of the functions $f$ and $g$ are strongly convex, a…

math.OC2024

Operator Splitting for Convex Constrained Markov Decision Processes

Panagiotis D. Grontas, Anastasios Tsiamis, John Lygeros

We consider finite Markov decision processes (MDPs) with convex constraints and known dynamics. In principle, this problem is amenable to off-the-shelf convex optimization solvers,…

math.OC2024

BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent

Panagiotis D. Grontas, Giuseppe Belgioioso, Carlo Cenedese +3

Hierarchical decision making problems, such as bilevel programs and Stackelberg games, are attracting increasing interest in both the engineering and machine learning communities.…