Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions

@article{diaa2024,
  title = {Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions},
  author = {Abdulrahman Diaa and Lucas Fenaux and Thomas Humphries and Marian Dietz and Faezeh Ebrahimianghazani and Bailey Kacsmar and Xinda Li and Nils Lukas and Rasoul Akhavan Mahdavi and Simon Oya and Ehsan Amjadian and Florian Kerschbaum},
  journal = {USENIX Security Symposium},
  year = {2024},
  month = {Jan},
}

Abdulrahman Diaa et al. (2024). Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. USENIX Security Symposium.

Abdulrahman Diaa, et al.. "Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions." USENIX Security Symposium, 2024.

Abdulrahman Diaa, et al.. "Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions." USENIX Security Symposium (2024).

Abdulrahman Diaa et al., 2024. Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions. USENIX Security Symposium.

TY  - JOUR
TI  - Fast and Private Inference of Deep Neural Networks by Co-designing Activation Functions
AU  - Abdulrahman Diaa
AU  - Lucas Fenaux
AU  - Thomas Humphries
AU  - Marian Dietz
AU  - Faezeh Ebrahimianghazani
AU  - Bailey Kacsmar
AU  - Xinda Li
AU  - Nils Lukas
AU  - Rasoul Akhavan Mahdavi
AU  - Simon Oya
AU  - Ehsan Amjadian
AU  - Florian Kerschbaum
PY  - 2024
JO  - USENIX Security Symposium
ER  -