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TableĀ 1 Quantum resource requirements for different schemes. The resource requirements for performing training and prediction are defined in term of the number of linear optical element (i.e. beam splitters and phase shifters) settings required, where N is the number of training data, D is the dimension of the data features, M is the number of trainable circuit and observable parameters, and R is the number of random Fourier features

From: Fock state-enhanced expressivity of quantum machine learning models

Schemes Training Prediction
Variational methods O(NDM) D
Kernel methods \(O(N^{2})\) N
Random kitchen sinks O(NR) R