Hybrid QML models trained with classical DP-SGD retain higher accuracy than classical models under fixed privacy budgets on synthetic and image-classification tasks.
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ALAC formulates accelerometer calibration as a constrained homogeneous least-squares problem on a combined error matrix, recovering scale, misalignment, and bias parameters from five attitude-aided measurements under static gravity.
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Private training in quantum machine learning
Hybrid QML models trained with classical DP-SGD retain higher accuracy than classical models under fixed privacy budgets on synthetic and image-classification tasks.