Learnability of Quantum Neural Networks
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao
Abstract
The learnability of quantum neural network, which includes its convergence behavior in optimization and the ability to efficiently learn classes of computationally hard concepts is investigated, providing theoretical guidance for developing advanced protocols in the NISQ era.
Topics & Concepts
LearnabilityComputer scienceArtificial neural networkConvergence (economics)QuantumTheoretical computer scienceArtificial intelligenceMachine learningQuantum mechanicsPhysicsEconomicsEconomic growthQuantum Computing Algorithms and ArchitectureQuantum Information and CryptographyNeural Networks and Applications