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Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation
  With Two-Way Mixup

Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup

17 June 2020
Seungeun Oh
Jihong Park
Eunjeong Jeong
Hyesung Kim
M. Bennis
Seong-Lyun Kim
    FedML
ArXivPDFHTML

Papers citing "Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup"

11 / 11 papers shown
Title
Federated Learning-Distillation Alternation for Resource-Constrained IoT
Federated Learning-Distillation Alternation for Resource-Constrained IoT
Rafael Valente da Silva
Onel L. A. López
R. D. Souza
19
0
0
26 May 2025
Advances and Open Problems in Federated Learning
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
108
6,177
0
10 Dec 2019
Distilling On-Device Intelligence at the Network Edge
Distilling On-Device Intelligence at the Network Edge
Jihong Park
Shiqiang Wang
Anis Elgabli
Seungeun Oh
Eunjeong Jeong
Han Cha
Hyesung Kim
Seong-Lyun Kim
M. Bennis
36
32
0
16 Aug 2019
Federated Reinforcement Distillation with Proxy Experience Memory
Federated Reinforcement Distillation with Proxy Experience Memory
Han Cha
Jihong Park
Hyesung Kim
Seong-Lyun Kim
M. Bennis
54
16
0
15 Jul 2019
Multi-hop Federated Private Data Augmentation with Sample Compression
Multi-hop Federated Private Data Augmentation with Sample Compression
Eunjeong Jeong
Seungeun Oh
Jihong Park
Hyesung Kim
M. Bennis
Seong-Lyun Kim
51
17
0
15 Jul 2019
Wireless Federated Distillation for Distributed Edge Learning with
  Heterogeneous Data
Wireless Federated Distillation for Distributed Edge Learning with Heterogeneous Data
Jinhyun Ahn
Osvaldo Simeone
Joonhyuk Kang
FedML
33
109
0
05 Jul 2019
Federated Machine Learning: Concept and Applications
Federated Machine Learning: Concept and Applications
Qiang Yang
Yang Liu
Tianjian Chen
Yongxin Tong
FedML
52
2,302
0
13 Feb 2019
Wireless Network Intelligence at the Edge
Wireless Network Intelligence at the Edge
Jihong Park
S. Samarakoon
M. Bennis
Mérouane Debbah
87
519
0
07 Dec 2018
Communication-Efficient On-Device Machine Learning: Federated
  Distillation and Augmentation under Non-IID Private Data
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
Eunjeong Jeong
Seungeun Oh
Hyesung Kim
Jihong Park
M. Bennis
Seong-Lyun Kim
FedML
54
596
0
28 Nov 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
236
9,687
0
25 Oct 2017
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
236
19,523
0
09 Mar 2015
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