Precise Approximation of Convolutional Neural Networks for Homomorphically Encrypted Data-Reference-Cited by-同舟云学术

Precise Approximation of Convolutional Neural Networks for Homomorphically Encrypted Data

Published:2023 Issue: Volume:11 Page:62062-62076
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Lee Junghyun¹^ORCID,Lee Eunsang²^ORCID,Lee Joon-Woo³^ORCID,Kim Yongjune⁴^ORCID,Kim Young-Sik⁵^ORCID,No Jong-Seon¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, INMC, Seoul National University, Seoul, Republic of Korea

2. Department of Software, Sejong University, Seoul, Republic of Korea

3. Department of Computer Science and Engineering, Chung-Ang University, Seoul, Republic of Korea

4. Department of Electrical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea

5. Department of Information and Communication Engineering, Chosun University, Gwangju, Republic of Korea

Funder

National Research Foundation of Korea

Korea Government

Ministry of Science and ICT, South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10155408.pdf?arnumber=10155408

Reference38 articles.

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4. Sur La détermination des polyn&ohat;mes d’approximation de degré donnée;remez;Commun Soc Math Kharkov,1934

5. Very deep convolutional networks for large-scale image recognition;simonyan;Proc Int Conf Learn Represent (ICLR),2015

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1. Self-learning activation functions to increase accuracy of privacy-preserving Convolutional Neural Networks with homomorphic encryption;PLOS ONE;2024-07-22

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