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NN-EMD: Efficiently Training Neural Networks using Encrypted
  Multi-Sourced Datasets

NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets

18 December 2020
Runhua Xu
J. Joshi
Chao Li
    FedML
ArXivPDFHTML

Papers citing "NN-EMD: Efficiently Training Neural Networks using Encrypted Multi-Sourced Datasets"

4 / 4 papers shown
Title
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation
Qianren Mao
Qili Zhang
Hanwen Hao
Zhentao Han
Runhua Xu
...
Jing Chen
Yangqiu Song
Jin Dong
Jianxin Li
Philip S. Yu
71
1
0
27 Apr 2025
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
Runhua Xu
Bo Li
Chao Li
J. Joshi
Shuai Ma
Jianxin Li
FedML
38
10
0
10 Jan 2025
Edge Deep Learning Model Protection via Neuron Authorization
Edge Deep Learning Model Protection via Neuron Authorization
Jinyin Chen
Haibin Zheng
T. Liu
Rongchang Li
Yao Cheng
Xuhong Zhang
S. Ji
FedML
23
0
0
22 Mar 2023
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
29
100
0
10 Aug 2021
1