JOURNAL ARTICLE

Quantum Machine Learning: A Survey

Pramoda Medisetty

Year: 2024 Journal:   Journal of Electrical Systems Vol: 20 (6s)Pages: 971-981

Abstract

Quantum Machine Learning (QML) is an emergent discipline that integrates the principles of quantum computing with traditional machine learning techniques, aiming to enhance the capabilities of data analysis and decision-making processes. Leveraging the unique properties, QML promises to revolutionize machine learning by offering superior processing power and computational efficiency. The synergistic approach followed by each Quantum Machine Learning Algorithm allows for the management of large databases and the execution of complex computational tasks more efficiently than classical algorithms. The integration of QML into machine learning workflows can lead to the development of advanced AI systems capable of personalized treatment recommendations, scientific discovery, and data-driven decision-making, thereby transforming the landscape of artificial intelligence and decision-making processes.

Keywords:
Computer science Quantum machine learning Quantum Artificial intelligence Psychology Physics Quantum computer Quantum mechanics

Metrics

3
Cited By
1.92
FWCI (Field Weighted Citation Impact)
12
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Quantum Computing Algorithms and Architecture
Physical Sciences →  Computer Science →  Artificial Intelligence
Quantum Information and Cryptography
Physical Sciences →  Computer Science →  Artificial Intelligence
Quantum Mechanics and Applications
Physical Sciences →  Physics and Astronomy →  Atomic and Molecular Physics, and Optics
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