Web: http://arxiv.org/abs/2205.03057

May 9, 2022, 1:11 a.m. | Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D. Scherer, Axel Plinge, Christopher Mutschler

cs.LG updates on arXiv.org arxiv.org

The data representation in a machine-learning model strongly influences its
performance. This becomes even more important for quantum machine learning
models implemented on noisy intermediate scale quantum (NISQ) devices. Encoding
high dimensional data into a quantum circuit for a NISQ device without any loss
of information is not trivial and brings a lot of challenges. While simple
encoding schemes (like single qubit rotational gates to encode high dimensional
data) often lead to information loss within the circuit, complex encoding
schemes …

arxiv classification data incremental quantum

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