SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing

14 November 2022

Papers citing "SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing"

4 / 4 papers shown

Title
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 152 349 0 25 Sep 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 94 110 0 25 Feb 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy Nicolas Papernot Abhradeep Thakurta Shuang Song Steve Chien Ulfar Erlingsson AAML 139 178 0 28 Jul 2020
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 252 36,362 0 25 Aug 2016