Quantum Machine Learning Algorithms

Renata Wong, Tanya Garg, Ritu Thombre, Alberto Maldonado Romo, P. N. Niranjan, Pinaki Sen, Mandeep Kaur Saggi, Amandeep Singh Bhatia

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

In recent times, the combination of machine learning and quantum computing has been applied greatly to solve the problems of intelligent computing. The new emerging area of quantum machine learning can be exploited to great extent for accelerating the existing classical machine learning algorithms for accurate classifications and better predictions of massive data. Quantum computing and machine learning are anticipated to play a crucial part in how the community deals with information in the future. The objective of this chapter is to highlight the present evolution of quantum computers in the setting of intelligent data mining. Recent progress in quantum algorithms can act as a stepping stone for quantum machine learning models. The determination relative merits of classical and quantum machine learning models would depend on the current and future prospects of quantum computing. However, the implementation of quantum algorithms needs quantum hardware that is not yet accessible on a wide scale.

Original languageEnglish
Title of host publicationEmerging Computing Paradigms
Subtitle of host publicationPrinciples, Advances and Applications
Publisherwiley
Pages79-98
Number of pages20
ISBN (Electronic)9781119813439
ISBN (Print)9781119813415
DOIs
StatePublished - 01 01 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 John Wiley & Sons, Ltd.

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