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2009.05537
Cited By
Federated Model Distillation with Noise-Free Differential Privacy
11 September 2020
Lichao Sun
Lingjuan Lyu
FedML
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Papers citing
"Federated Model Distillation with Noise-Free Differential Privacy"
20 / 20 papers shown
Title
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
Shuya Feng
Meisam Mohammady
Hanbin Hong
Shenao Yan
Ashish Kundu
Binghui Wang
Yuan Hong
FedML
44
3
0
20 Jul 2024
Federated learning with differential privacy and an untrusted aggregator
Kunlong Liu
Trinabh Gupta
47
0
0
17 Dec 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency
Jiawei Shao
Zijian Li
Wenqiang Sun
Tailin Zhou
Yuchang Sun
Lumin Liu
Zehong Lin
Yuyi Mao
Jun Zhang
FedML
43
23
0
20 Jul 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges
Mang Ye
Xiuwen Fang
Bo Du
PongChi Yuen
Dacheng Tao
FedML
AAML
39
248
0
20 Jul 2023
Towards the Flatter Landscape and Better Generalization in Federated Learning under Client-level Differential Privacy
Yi Shi
Kang Wei
Li Shen
Yingqi Liu
Xueqian Wang
Bo Yuan
Dacheng Tao
FedML
38
2
0
01 May 2023
Zero-Knowledge Proof-based Practical Federated Learning on Blockchain
Zhibo Xing
Zijian Zhang
Meng Li
Jing Liu
Liehuang Zhu
Giovanni Russello
M. R. Asghar
16
17
0
12 Apr 2023
Decentralized Learning with Multi-Headed Distillation
A. Zhmoginov
Mark Sandler
Nolan Miller
Gus Kristiansen
Max Vladymyrov
FedML
40
4
0
28 Nov 2022
Towards Efficient Communications in Federated Learning: A Contemporary Survey
Zihao Zhao
Yuzhu Mao
Yang Liu
Linqi Song
Ouyang Ye
Xinlei Chen
Wenbo Ding
FedML
54
60
0
02 Aug 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms
Ehsan Hallaji
R. Razavi-Far
M. Saif
AAML
FedML
24
13
0
05 Jul 2022
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer
Yae Jee Cho
Jianyu Wang
Tarun Chiruvolu
Gauri Joshi
FedML
35
30
0
16 Sep 2021
Source Inference Attacks in Federated Learning
Hongsheng Hu
Z. Salcic
Lichao Sun
Gillian Dobbie
Xuyun Zhang
27
79
0
13 Sep 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models
Lan Zhang
Dapeng Wu
Xiaoyong Yuan
FedML
38
47
0
08 Sep 2021
FedKD: Communication Efficient Federated Learning via Knowledge Distillation
Chuhan Wu
Fangzhao Wu
Lingjuan Lyu
Yongfeng Huang
Xing Xie
FedML
27
373
0
30 Aug 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning
Zhuangdi Zhu
Junyuan Hong
Jiayu Zhou
FedML
27
630
0
20 May 2021
Federated Multi-View Learning for Private Medical Data Integration and Analysis
Sicong Che
Hao Peng
Lichao Sun
Yong Chen
Lifang He
FedML
63
40
0
04 May 2021
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges
Mingzhe Chen
Deniz Gündüz
Kaibin Huang
Walid Saad
M. Bennis
Aneta Vulgarakis Feljan
H. Vincent Poor
38
401
0
05 Apr 2021
FedMood: Federated Learning on Mobile Health Data for Mood Detection
Xiaohang Xu
Hao Peng
Lichao Sun
Md. Zakirul Alam Bhuiyan
Lianzhong Liu
Lifang He
FedML
46
53
0
06 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu
Han Yu
Xingjun Ma
Chen Chen
Lichao Sun
Jun Zhao
Qiang Yang
Philip S. Yu
FedML
183
355
0
07 Dec 2020
Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness
Lingjuan Lyu
Xuanli He
Yitong Li
35
89
0
03 Oct 2020
Threats to Federated Learning: A Survey
Lingjuan Lyu
Han Yu
Qiang Yang
FedML
202
434
0
04 Mar 2020
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