1 citations · 1 across the 5 of their papers we have counts for
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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…