Partial Least-Squares Quantum Optimization
By Parth Gupta
Previously, I used a partial least squares (PLS) implementation to predict March Madness brackets, called the Massey Method. I learned that, although accurate, it was a very slow algorithm. My ultimate goal for this project is to optimize the classical implementation of a least squares algorithm using the Quantum Approximate Optimization Algorithm (QAOA). The classical least squares implementation would take too long for a computer to diagnose the patient. Instead, the doctor would have to make an educated prediction and hope their treatment would sufficiently aid the patient. With a QAOA implementation of PLS, the doctor would receive a quick and accurate diagnosis, enabling them to administer treatment quickly and correctly, potentially saving the patient’s life. Of course, this is just one example of the power of this algorithm and can be applied to many other scenarios.