Support Vector Machines on Noisy Intermediate Scale Quantum Computers

Understand

Support vector machine algorithms are considered essential for the implementation of automation in a radio access network.

• Specifically, they are critical in the prediction of the quality of user experience for video streaming based on device and network-level metrics.
• Quantum SVM is the quantum analogue of the classical SVM algorithm, which utilizes the properties of quantum computers to speed up the algorithm exponentially.
• In this work, we derive an optimized preprocessing unit for a quantum SVM that allows classifying any two-dimensional datasets that are linearly separable.