70 citations · 271 across the 35 of their papers we have counts for
43 papers
Training Variational Quantum Algorithms Is NP-Hard, Even Locally
Dax Enshan Koh, Triscia Mundo, Iosif Sakos +1
Variational quantum algorithms (VQAs) generally rely on classical optimization to train parameterized quantum circuits. This training seeks to minimize an objective function, and i…
Global Optimization for Parametrized Quantum Circuits
Iosif Sakos, Antonios Varvitsiotis, Georgios Korpas +1
In the absence of error correction, noisy intermediate-scale quantum devices are operated by training parametrized quantum circuits (PQCs) so as to minimize a suitable loss functio…
Convex Markov Games and Beyond: New Proof of Existence, Characterization and Learning Algorithms for Nash Equilibria
Anas Barakat, Ioannis Panageas, Antonios Varvitsiotis
Convex Markov Games (cMGs) were recently introduced as a broad class of multi-agent learning problems that generalize Markov games to settings where strategic agents optimize gener…
Certifying Concavity and Monotonicity in Games via Sum-of-Squares Hierarchies
Vincent Leon, Iosif Sakos, Ryann Sim +1
Concavity and its refinements underpin tractability in multiplayer games, where players independently choose actions to maximize their own payoffs which depend on other players' ac…
Nash equilibria in semidefinite games and Lemke-Howson paths
Constantin Ickstadt, Thorsten Theobald, Elias Tsigaridas +1
We consider an algorithmic framework for two-player non-zero-sum semidefinite games, where each player's strategy is a positive semidefinite matrix with trace one. We formulate the…
Online Multi-Agent Control with Adversarial Disturbances
Anas Barakat, John Lazarsfeld, Georgios Piliouras +1
Online multi-agent control problems, where many agents pursue competing and time-varying objectives, are widespread in domains such as autonomous robotics, economics, and energy sy…