A Differentially Private Framework for Deep Learning with Convexified Loss Functions

3 April 2022

Papers citing "A Differentially Private Framework for Deep Learning with Convexified Loss Functions"

6 / 6 papers shown

Title
Practical, Private Assurance of the Value of Collaboration H. Asghar Zhigang Lu Zhongrui Zhao Dali Kaafar FedML 21 0 0 04 Oct 2023
Differentially Private Topological Data Analysis Taegyu Kang Sehwan Kim Jinwon Sohn Jordan Awan 19 3 0 05 May 2023
A Systematic Literature Review On Privacy Of Deep Learning Systems Vishal Jignesh Gandhi Sanchit Shokeen Saloni Koshti PILM 11 1 0 07 Dec 2022
Directional Privacy for Deep Learning Pedro Faustini Natasha Fernandes Shakila Mahjabin Tonni Annabelle McIver Mark Dras 14 1 0 09 Nov 2022
Additive Logistic Mechanism for Privacy-Preserving Self-Supervised Learning Yunhao Yang Parham Gohari Ufuk Topcu 12 1 0 25 May 2022
On the Privacy Risks of Deploying Recurrent Neural Networks in Machine Learning Models Yunhao Yang Parham Gohari Ufuk Topcu AAML 28 3 0 06 Oct 2021