Inductive supervised quantum learning

Understand

In supervised learning, an inductive learning algorithm extracts general rules from observed training instances, then the rules are applied to test instances.

• We show that this splitting of training and application arises naturally, in the classical setting, from a simple independence requirement with a physical interpretation of being non-signalling.
• Thus, two seemingly different definitions of inductive learning happen to coincide.
• This follows from the properties of classical information that break down in the quantum setup.