Dealing with categorical data is an essential part of data preprocessing in many machine learning tasks. Fortunately, encoding categorical data efficiently helps enhance the performance of machine ...

One of the key obstacles to efficient quantum machine learning has been encoding classical data into quantum states, a computationally challenging task requiring deeply entangled circuits. To ...

The team’s focus on encoding classical data for use by quantum algorithms is a stepping stone toward progress in leveraging quantum information science and technology (QIST) methods as part of ...

The key to this data-encoding method lies in Unicode's "variation selectors." These 256 special codepoints labeled VS-1 through VS-256 have no visible representation but can modify the ...

The multi-basis graph encoding method is a novel quantum encoding strategy that effectively represents high-dimensional optimization problems with a limited number of qubits. In HOLO's approach ...