5 papers
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…
Optimistic Online Learning in Symmetric Cone Games
Anas Barakat, Wayne Lin, John Lazarsfeld +1
We introduce symmetric cone games (SCGs), a broad class of multi-player games where each player's strategy lies in a generalized simplex (the trace-one slice of a symmetric cone).…
Learning in Quantum Common-Interest Games and the Separability Problem
Wayne Lin, Georgios Piliouras, Ryann Sim +1
Learning in games has emerged as a powerful tool for machine learning with numerous applications. Quantum games model interactions between strategic players who have access to quan…
Learning and steering game dynamics towards desirable outcomes
Ilayda Canyakmaz, Iosif Sakos, Wayne Lin +2
Game dynamics, which describe how agents' strategies evolve over time based on past interactions, can exhibit a variety of undesirable behaviours including convergence to suboptima…
No-Regret Learning and Equilibrium Computation in Quantum Games
Wayne Lin, Georgios Piliouras, Ryann Sim +1
As quantum processors advance, the emergence of large-scale decentralized systems involving interacting quantum-enabled agents is on the horizon. Recent research efforts have explo…