Not just about privacy

By B. Goold. 2020

4 citations recorded by the source corpus.

Subfields: Political Science and International Relations, Sociology and Political Science

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Political Science and International Relations

1. Ali Jalali
2. Ramesh Raskar
3. Fatemehsadat Mirshghallah
4. Hadi Esmaeilzadeh
5. Dean M. Tullsen
6. Bashir I. Morshed
7. Abhishek Singh
8. Syed Kamrul Islam

In Sociology and Political Science

1. Ali Jalali
2. Ramesh Raskar
3. Fatemehsadat Mirshghallah
4. Hadi Esmaeilzadeh
5. Dean M. Tullsen
6. Bashir I. Morshed
7. Abhishek Singh
8. Syed Kamrul Islam

Citations in the corpus

• Privacy in Deep Learning: A Survey (2020, methodology): “ARDEN [106] # # # MNIST, CIFAR-10, SVHN Image Classification w/ DNN Cloak [107] # # CIFAR-100, CelebA, UTKFace Image Classification w/ DNN Cryptonets [108] # # # MNIST Image Classification w/ DNN Private Classification [109] # # # MNIST Image Classification w/ DNN TAPAS [110] # # # MNIST, Faces, Can”
• Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review (2023, methodology): “Researchers proposed different techniques for appropriately performing the DL model splitting, such as differential private mechanism [365], Arden (privAte infeRence framework based on DNNs) [366], and hybrid edge-cloud framework [367].”
• A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference (2020, methodology): “Wang et al. (Wang et al., 2018) propose a noise injection framework that randomly nullifies input elements for private inference, but their method requires retraining of the entire network.”