Not All Features Are Equal: Discovering Essential Features for
Preserving Prediction Privacy

Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy

26 March 2020

Fatemehsadat Mireshghallah

Mohammadkazem Taram

Ahmed T. Elthakeb

Dean Tullsen

H. Esmaeilzadeh

Papers citing "Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy"

5 / 5 papers shown

Title
Privacy-preserving Security Inference Towards Cloud-Edge Collaborative Using Differential Privacy Yulong Wang Xingshu Chen Qixu Wang FedML 26 3 0 13 Dec 2022
Task-aware Privacy Preservation for Multi-dimensional Data Jiangnan Cheng A. Tang Sandeep P. Chinchali 28 7 0 05 Oct 2021
Subpopulation Data Poisoning Attacks Matthew Jagielski Giorgio Severi Niklas Pousette Harger Alina Oprea AAML SILM 24 112 0 24 Jun 2020
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware Florian Tramèr Dan Boneh FedML 114 395 0 08 Jun 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 674 0 17 Feb 2018