Federated Learning is Better with Non-Homomorphic Encryption

4 December 2023

Papers citing "Federated Learning is Better with Non-Homomorphic Encryption"

7 / 7 papers shown

Title
BurTorch: Revisiting Training from First Principles by Coupling Autodiff, Math Optimization, and Systems Konstantin Burlachenko Peter Richtárik AI4CE 39 0 0 18 Mar 2025
Privacy Preserving Federated Learning in Medical Imaging with Uncertainty Estimation Nikolas Koutsoubis Yasin Yilmaz Ravi P. Ramachandran M. Schabath Ghulam Rasool 34 8 0 18 Jun 2024
On Lattices, Learning with Errors, Random Linear Codes, and Cryptography O. Regev LRM 69 1,071 0 08 Jan 2024
Cross-Silo Federated Learning Across Divergent Domains with Iterative Parameter Alignment Matt Gorbett Hossein Shirazi Indrakshi Ray FedML 13 2 0 08 Nov 2023
FL_PyTorch: optimization research simulator for federated learning Konstantin Burlachenko Samuel Horváth Peter Richtárik FedML 29 18 0 07 Feb 2022
Permutation Compressors for Provably Faster Distributed Nonconvex Optimization Rafal Szlendak A. Tyurin Peter Richtárik 115 35 0 07 Oct 2021
The Power of Linear Reconstruction Attacks S. Kasiviswanathan M. Rudelson Adam D. Smith AAML 57 54 0 08 Oct 2012