International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 5 September-October 2024 Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

Quantum Machine Learning: Leveraging Quantum Computing for Enhanced Learning Algorithms

Author(s) Sonia Rani, Ravinder Kaur, Chitra Desai, R.P.Ambilwade
Country India
Abstract The paper "Quantum Machine Learning: Leveraging Quantum Computing for Enhanced Learning Algorithms" explores the integration of quantum computing principles into classical machine learning techniques, aiming to address limitations such as scalability and computational inefficiency. It presents the foundational concepts of quantum computing, including superposition and entanglement, and their application in accelerating machine learning processes. The study emphasizes the potential for quantum algorithms to significantly improve the performance of machine learning tasks by processing large datasets more efficiently and exploring larger hypothesis spaces.
Key quantum machine learning algorithms discussed include Quantum Support Vector Machines (QSVM), Quantum Principal Component Analysis (QPCA), and Quantum Neural Networks (QNN), each of which leverages quantum mechanics to overcome the computational barriers faced by classical algorithms. The Quantum Approximate Optimization Algorithm (QAOA) is also highlighted for its ability to optimize machine learning models more effectively. While the theoretical benefits of Quantum Machine Learning (QML) are promising, the practical application of these techniques is currently limited by the constraints of existing quantum hardware. This research contributes to the emerging field of QML by examining its potential advantages and future implications in addressing complex data processing challenges.
Keywords Keywords - Quantum Machine Learning (QML), Quantum Computing Algorithms, Quantum Support Vector Machines (QSVM), Quantum Neural Networks (QNN), Quantum Approximate Optimization Algorithm (QAOA).
Field Engineering
Published In Volume 6, Issue 5, September-October 2024
Published On 2024-09-13
Cite This Quantum Machine Learning: Leveraging Quantum Computing for Enhanced Learning Algorithms - Sonia Rani, Ravinder Kaur, Chitra Desai, R.P.Ambilwade - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.27450
DOI https://doi.org/10.36948/ijfmr.2024.v06i05.27450
Short DOI https://doi.org/gzwp3s

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