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Personalized and Private Peer-to-Peer Machine Learning
23 May 2017
A. Bellet
R. Guerraoui
Mahsa Taziki
Marc Tommasi
FedML
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Papers citing
"Personalized and Private Peer-to-Peer Machine Learning"
9 / 9 papers shown
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILM
MIACV
329
95
0
04 Jul 2021
A Privacy-Preserving and Trustable Multi-agent Learning Framework
Anudit Nagar
Cuong Tran
Ferdinando Fioretto
155
1
0
02 Jun 2021
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
Matthias Paulik
M. Seigel
Henry Mason
Dominic Telaar
Joris Kluivers
...
Dominic Hughes
O. Javidbakht
Fei Dong
Rehan Rishi
Stanley Hung
FedML
453
141
0
16 Feb 2021
A(DP)
2
^2
2
SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
Jie Xu
Wei Zhang
Haiwei Yang
FedML
198
12
0
21 Aug 2020
FedCD: Improving Performance in non-IID Federated Learning
Kavya Kopparapu
Eric Lin
Jessica Zhao
FedML
436
41
0
17 Jun 2020
Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019
Xueru Zhang
Mohammad Mahdi Khalili
M. Liu
FedML
231
26
0
08 Oct 2019
Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting
Clement Fung
Jamie Koerner
Stewart Grant
Ivan Beschastnikh
OOD
FedML
216
12
0
23 Nov 2018
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms
Xueru Zhang
Mohammad Mahdi Khalili
M. Liu
198
30
0
07 Oct 2018
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang
Mohammad Mahdi Khalili
M. Liu
FedML
299
94
0
06 Jun 2018
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