Quantum Semantic Learning by Reverse Annealing of an Adiabatic Quantum Computer
Quantum Semantic Learning by Reverse Annealing of an Adiabatic Quantum Computer
Abstract Restricted Boltzmann machines (RBMs) constitute a class of neural networks for unsupervised learning with applications ranging from pattern classification to quantum state reconstruction. Despite the potential representative power, the diffusion of RBMs is quite limited since their training process proves to be hard. The advent of commercial adiabatic quantum …