Boosting Quantum Machine Learning Algorithms via Coordinate Transformations

A generic strategy to accelerate and improve the overall performance of gradient-based optimization methods in quantum machine learning, by introducing coordinate transformations that allow to explore the configuration landscape more efficiently and alleviate the effects of barren plateaus and local minima.