Online seminar #1: Quantum Approximate Optimization Algorithm for Bayesian network structure learning
Vicente P. Soloviev (UPM) Bayesian network structure learning is an NP-hard problem that has been faced by anumber of traditional approaches in recent decades. In this work, a specific type ofvariational quantum algorithm, the quantum approximate optimization algorithm, wasused to solve the Bayesian network structure learning problem. Our results showed thatthe quantum approximate optimization algorithm…
