@article{Ablayev2020, 
author = {Farid Ablayev and Marat Ablayev and Joshua Zhexue Huang and Kamil Khadiev and Nailya Salikhova and Dingming Wu},
title = {On Quantum Methods for Machine Learning Problems Part II: Quantum Classification Algorithms},
year = {2020},
journal = {Big Data Mining and Analytics},
volume = {3},
number = {1},
pages = {56-67},
keywords = {quantum classification, binary classification, nearest neighbor algorithm},
url = {https://www.sciopen.com/article/10.26599/BDMA.2019.9020018},
doi = {10.26599/BDMA.2019.9020018},
abstract = {This is a review of quantum methods for machine learning problems that consists of two parts. The first part, "quantum tools", presented some of the fundamentals and introduced several quantum tools based on known quantum search algorithms. This second part of the review presents several classification problems in machine learning that can be accelerated with quantum subroutines. We have chosen supervised learning tasks as typical classification problems to illustrate the use of quantum methods for classification.}
}