Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning-Reference-Cited by-同舟云学术

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Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning

Published:2024-06-09 Issue: Volume: Page:1121-1126
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Ju Keyi¹,Qin Xiaoqi¹,Zhong Hui²,Zhang Xinyue³,Pan Miao²,Liu Baoling¹

Affiliation:

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications,Beijing,China,100876

2. University of Houston,Department of Electrical and Computer Engineering,Houston,TX,77204

3. Kennesaw State University,Department of Computer Science,Marietta,GA,30060

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622663.pdf?arnumber=10622663

Reference15 articles.

1. Machine Learning Algorithms in Quantum Computing: A Survey

2. Quantum computing for energy systems optimization: Challenges and opportunities

3. Quantum machine learning

4. Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients

5. The Algorithmic Foundations of Differential Privacy

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