Quantum kernel methods match or exceed classical kernels on real-valued SAR chips for vessel classification but overfit and underperform when encoding complex-valued SAR data.
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Introduces DIP that encapsulates sample mixing inside the hypothesis class to reduce Rademacher complexity and improve generalization over standard Mixup.
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Maritime object classification with SAR imagery using quantum kernel methods
Quantum kernel methods match or exceed classical kernels on real-valued SAR chips for vessel classification but overfit and underperform when encoding complex-valued SAR data.
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Data Interpolating Prediction: Alternative Interpretation of Mixup
Introduces DIP that encapsulates sample mixing inside the hypothesis class to reduce Rademacher complexity and improve generalization over standard Mixup.