← all papers · overview

A Survey of Quantum Learning Theory

Abstract

This paper surveys quantum learning theory: the theoretical aspects of machine learning using quantum computers. We describe the main results known for three models of learning: exact learning from membership queries, and Probably Approximately Correct (PAC) and agnostic learning from classical or quantum examples.

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).