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Highly Accurate CNN Inference Using Approximate Activation Functions
  over Homomorphic Encryption

Highly Accurate CNN Inference Using Approximate Activation Functions over Homomorphic Encryption

8 September 2020
Takumi Ishiyama
Takuya Suzuki
Hayato Yamana
ArXivPDFHTML

Papers citing "Highly Accurate CNN Inference Using Approximate Activation Functions over Homomorphic Encryption"

4 / 4 papers shown
Title
Homomorphic WiSARDs: Efficient Weightless Neural Network training over
  encrypted data
Homomorphic WiSARDs: Efficient Weightless Neural Network training over encrypted data
Leonardo Neumann
Antonio Guimarães
Diego F. Aranha
Edson Borin
AAML
23
0
0
29 Mar 2024
HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic
  Encryption-Based Neural Networks
HyPHEN: A Hybrid Packing Method and Optimizations for Homomorphic Encryption-Based Neural Networks
Donghwan Kim
J. Park
Jongmin Kim
Sangpyo Kim
Jung Ho Ahn
27
17
0
05 Feb 2023
Private and Reliable Neural Network Inference
Private and Reliable Neural Network Inference
Nikola Jovanović
Marc Fischer
Samuel Steffen
Martin Vechev
22
14
0
27 Oct 2022
Precise Approximation of Convolutional Neural Networks for
  Homomorphically Encrypted Data
Precise Approximation of Convolutional Neural Networks for Homomorphically Encrypted Data
Junghyun Lee
Eunsang Lee
Joon-Woo Lee
Yongjune Kim
Young-Sik Kim
Jong-Seon No
16
56
0
23 May 2021
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