Quantum ensemble learning with a programmable superconducting processor

We present a quantum extension of the adaptive boosting (Adaboost) algorithm by using the probabilistic nature of quantum measurements. We implement our scheme on a programmable superconductor processor and observe significant performance improvements in quantum machine learning models, including quantum neural networks and quantum convolutional neural networks.