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quant-ph2026
A provable quantum advantage for approximate optimization via decoded quantum interferometry
Maximilian J. Kramer, Elies Gil-Fuster, Benjamin D. M. Jones +2
Decoded quantum interferometry (DQI) is a novel paradigm for tackling approximate optimization problems on quantum computers. This framework comes with strong performance guarantee…
quant-ph2026
A PAC-Bayesian approach to generalization for quantum models
Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert +3
Generalization is a central concept in machine learning theory, yet for quantum models, it is predominantly analyzed through uniform bounds that depend on a model's overall capacit…