There is a current void in understanding quantum learning advantages between two extreme cases (exponential advantage for uniform distributions, no advantage for adversarial distributions). Lewis et al. design an efficient quantum algorithm for learning periodic neurons over non-uniform distributions of classical data and show that this is hard for a broad class of classical algorithms, resulting in an exponential quantum advantage.
- Laura Lewis
- Dar Gilboa
- Jarrod R. McClean
