1 citations · 1 across the 5 of their papers we have counts for
8 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…
Recognizing Signomial Convexity is Hard
Rui Zheng, Iosif Sakos, Antonios Varvitsiotis
Signomials---finite sums of generalized monomials with real exponents---are a natural machine learning model, combining parsimonious representations of power laws, inverse relation…
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…
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…
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…
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
Iosif Sakos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Panayotis Mertikopoulos +1
A wide array of modern machine learning applications - from adversarial models to multi-agent reinforcement learning - can be formulated as non-cooperative games whose Nash equilib…
Data-Scarce Identification of Game Dynamics via Sum-of-Squares Optimization
Iosif Sakos, Antonios Varvitsiotis, Georgios Piliouras
Understanding how players adjust their strategies in games, based on their experience, is a crucial tool for policymakers. It enables them to forecast the system's eventual behavio…
Catastrophe by Design in Population Games: Destabilizing Wasteful Locked-in Technologies
Stefanos Leonardos, Iosif Sakos, Costas Courcoubetis +1
In multi-agent environments in which coordination is desirable, the history of play often causes lock-in at sub-optimal outcomes. Notoriously, technologies with a significant envir…