Tag
This paper proposes a quantum annealing enhanced Q-learning framework for remaining useful life prediction, using the D-Wave system to solve QUBO formulations for action selection. It outperforms classical and quantum baselines on NASA C-MAPSS and predictive maintenance datasets.
This paper proposes a quantum annealing approach that reformulates client selection in federated learning as a QUBO problem to defend against Byzantine attacks, showing improved detection accuracy over classical MultiKrum on sophisticated attacks, especially when combined with a MultiSignal ensemble.