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Measuring the Effects of Non-Identical Data Distribution for Federated
  Visual Classification

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

13 September 2019
T. Hsu
Qi
Matthew Brown
    FedML
ArXivPDFHTML

Papers citing "Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification"

9 / 209 papers shown
Title
Analysis and Optimal Edge Assignment For Hierarchical Federated Learning
  on Non-IID Data
Analysis and Optimal Edge Assignment For Hierarchical Federated Learning on Non-IID Data
N. Mhaisen
Alaa Awad
Amr M. Mohamed
A. Erbad
M. Guizani
FedML
50
12
0
10 Dec 2020
Accurate and Fast Federated Learning via Combinatorial Multi-Armed
  Bandits
Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits
Taehyeon Kim
Sangmin Bae
Jin-woo Lee
Se-Young Yun
FedML
21
15
0
06 Dec 2020
Can Federated Learning Save The Planet?
Can Federated Learning Save The Planet?
Xinchi Qiu
Titouan Parcollet
Daniel J. Beutel
Taner Topal
Akhil Mathur
Nicholas D. Lane
23
78
0
13 Oct 2020
Client Selection in Federated Learning: Convergence Analysis and
  Power-of-Choice Selection Strategies
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
Yae Jee Cho
Jianyu Wang
Gauri Joshi
FedML
33
400
0
03 Oct 2020
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized
  Data
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data
Qianqian Tong
Guannan Liang
J. Bi
FedML
33
27
0
14 Sep 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated
  Optimization
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Jianyu Wang
Qinghua Liu
Hao Liang
Gauri Joshi
H. Vincent Poor
MoMe
FedML
16
1,297
0
15 Jul 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive
  Strategies
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
David Enthoven
Zaid Al-Ars
FedML
60
50
0
01 Apr 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees
Richeng Jin
Yufan Huang
Xiaofan He
H. Dai
Tianfu Wu
FedML
22
63
0
25 Feb 2020
Differentially Private Learning with Adaptive Clipping
Differentially Private Learning with Adaptive Clipping
Galen Andrew
Om Thakkar
H. B. McMahan
Swaroop Ramaswamy
FedML
19
330
0
09 May 2019
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