Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric

8 August 2022

Papers citing "Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric"

7 / 7 papers shown

Title
Conformal-DP: Differential Privacy on Riemannian Manifolds via Conformal Transformation Peilin He Liou Tang M. Amin Rahimian James Joshi 33 0 0 29 Apr 2025
Random matrix theory improved Fréchet mean of symmetric positive definite matrices Florent Bouchard A. Mian Malik Tiomoko G. Ginolhac Frédéric Pascal 40 1 0 10 May 2024
Federated Learning on Riemannian Manifolds with Differential Privacy Zhenwei Huang Wen Huang Pratik Jawanpuria Bamdev Mishra FedML 42 6 0 15 Apr 2024
Gaussian Differential Privacy on Riemannian Manifolds Yangdi Jiang Xiaotian Chang Yi Liu Lei Ding Linglong Kong Bei Jiang 31 6 0 09 Nov 2023
DPZero: Private Fine-Tuning of Language Models without Backpropagation Liang Zhang Bingcong Li K. K. Thekumparampil Sewoong Oh Niao He 28 11 0 14 Oct 2023
Rieoptax: Riemannian Optimization in JAX Saiteja Utpala Andi Han Pratik Jawanpuria Bamdev Mishra 21 3 0 10 Oct 2022
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 188 651 0 27 Oct 2021