Keywords
quantum algorithm, quantum programming, machine learning
Abstract
This is a review of quantum methods for machine learning problems that consists of two parts. The first part, "quantum tools", presents the fundamentals of qubits, quantum registers, and quantum states, introduces important quantum tools based on known quantum search algorithms and SWAP-test, and discusses the basic quantum procedures used for quantum search methods. The second part, "quantum classification algorithms", introduces several classification problems that can be accelerated by using quantum subroutines and discusses the quantum methods used for classification.
Publisher
Tsinghua University Press
Recommended Citation
Farid Ablayev, Marat Ablayev, Joshua Zhexue Huang et al. On Quantum Methods for Machine Learning Problems Part I: Quantum Tools. Big Data Mining and Anyalytics 2020, 03(01): 41-55.