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On Quantum Methods for Machine Learning Problems Part II: Quantum Classification Algorithms

delete2020-03-01
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OA
AI
F
Farid Ablayev
M
Marat Ablayev
J
Joshua Zhexue Huang
K
Kamil Khadiev
D
Dingming Wu *
DOI:10.26599/BDMA.2019.9020018delete
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Abstract

Abstract

En 中文
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.
Keywords:
quantum classification
binary classification
nearest neighbor algorithm
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Journal

Big Data Mining and Analytics cover
Big Data Mining and Analytics
IF:
6.2
Papers:
274
Citations:
1.0K

Organization

K
Kazan Federal University
Scholars:
4.4K
Papers: 2.6K
Citations: 4.0K
S
shenzhen university
Scholars:
4.5W
Papers: 3.4W
Citations: 72