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WAFFLe: Weight Anonymized Factorization for Federated Learning

WAFFLe: Weight Anonymized Factorization for Federated Learning

13 August 2020
Weituo Hao
Nikhil Mehta
Kevin J. Liang
Pengyu Cheng
Mostafa El-Khamy
Lawrence Carin
    FedML
ArXiv (abs)PDFHTML

Papers citing "WAFFLe: Weight Anonymized Factorization for Federated Learning"

4 / 4 papers shown
Title
Fairness and Privacy-Preserving in Federated Learning: A Survey
Fairness and Privacy-Preserving in Federated Learning: A Survey
Taki Hasan Rafi
Faiza Anan Noor
Tahmid Hussain
Dong-Kyu Chae
FedML
114
50
0
14 Jun 2023
What Do We Mean by Generalization in Federated Learning?
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan
Warren Morningstar
Lin Ning
K. Singhal
OODFedML
123
76
0
27 Oct 2021
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
AutoFL: Enabling Heterogeneity-Aware Energy Efficient Federated Learning
Young Geun Kim
Carole-Jean Wu
102
87
0
16 Jul 2021
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Weituo Hao
Mostafa El-Khamy
Jungwon Lee
Jianyi Zhang
Kevin J. Liang
Changyou Chen
Lawrence Carin
FedML
70
91
0
27 Apr 2021
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