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We provide a complete work-flow, based on the language of quantum informationtheory, suitable for processing data for the purpose of pattern recognition.The main advantage of the introduced scheme is that it can be easilyimplemented and applied to process real-world data using modest computationresources. At the same time it can be used to investigate the difference in thepattern recognition resulting from the utilization of the tensor productstructure of the space of quantum states. We illustrate this difference byproviding a simple example based on the classification of 2D data.

Separable and non-separable data representation for pattern discrimination