Adiabatic Quantum Linear Regression

Understand

A major challenge in machine learning is the computational expense of training these models.

• Model training can be viewed as a form of optimization used to fit a machine learning model to a set of data, which can take up significant amount of time on classical computers.
• Adiabatic quantum computers have been shown to excel at solving optimization problems, and therefore, we believe, present a promising alternative to improve machine learning training times.
• In this paper, we present an adiabatic quantum computing approach for training a linear regression model.