Joint Optimization of Circuit Depth and Training Data in Quantum Classifiers
A study examines the combination of gate-by-gate circuit growth strategies and data-size bounds to jointly optimize quantum classifiers.
A study examines the combination of gate-by-gate circuit growth strategies and data-size bounds to jointly optimize quantum classifiers.