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TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based
  Clustering
v1v2v3 (latest)

TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering

16 September 2024
Rasoul Jafari Gohari
Laya Aliahmadipour
Ezat Valipour
    FedML
ArXiv (abs)PDFHTML

Papers citing "TPFL: Tsetlin-Personalized Federated Learning with Confidence-Based Clustering"

15 / 15 papers shown
Title
Clustered Federated Learning Architecture for Network Anomaly Detection
  in Large Scale Heterogeneous IoT Networks
Clustered Federated Learning Architecture for Network Anomaly Detection in Large Scale Heterogeneous IoT Networks
Xabier Sáez-de-Cámara
Jose Luis Flores
Cristóbal Arellano
A. Urbieta
Urko Zurutuza
62
56
0
28 Mar 2023
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating
FedSoft: Soft Clustered Federated Learning with Proximal Local Updating
Yichen Ruan
Carlee Joe-Wong
FedML
73
95
0
11 Dec 2021
Local Learning Matters: Rethinking Data Heterogeneity in Federated
  Learning
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matías Mendieta
Taojiannan Yang
Pu Wang
Minwoo Lee
Zhengming Ding
Chong Chen
FedML
101
163
0
28 Nov 2021
Multi-Center Federated Learning: Clients Clustering for Better Personalization
Guodong Long
Ming Xie
Tao Shen
Dinesh Manocha
Xianzhi Wang
Jing Jiang
Chengqi Zhang
FedML
60
251
0
19 Aug 2021
Federated Learning on Non-IID Data: A Survey
Federated Learning on Non-IID Data: A Survey
Hangyu Zhu
Jinjin Xu
Shiqing Liu
Yaochu Jin
OODFedML
84
794
0
12 Jun 2021
Clustered Sampling: Low-Variance and Improved Representativity for
  Clients Selection in Federated Learning
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni
Richard Vidal
Laetitia Kameni
Marco Lorenzi
FedML
60
193
0
12 May 2021
Towards Personalized Federated Learning
Towards Personalized Federated Learning
A. Tan
Han Yu
Li-zhen Cui
Qiang Yang
FedMLAI4CE
325
870
0
01 Mar 2021
Achieving Security and Privacy in Federated Learning Systems: Survey,
  Research Challenges and Future Directions
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
Alberto Blanco-Justicia
J. Domingo-Ferrer
Sergio Martínez
David Sánchez
Adrian Flanagan
K. E. Tan
FedML
53
113
0
12 Dec 2020
Three Approaches for Personalization with Applications to Federated
  Learning
Three Approaches for Personalization with Applications to Federated Learning
Yishay Mansour
M. Mohri
Jae Hun Ro
A. Suresh
FedML
131
576
0
25 Feb 2020
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task
  Optimization under Privacy Constraints
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler
K. Müller
Wojciech Samek
FedML
149
1,005
0
04 Oct 2019
Measuring the Effects of Non-Identical Data Distribution for Federated
  Visual Classification
Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
T. Hsu
Qi
Matthew Brown
FedML
143
1,150
0
13 Sep 2019
Robust Federated Learning in a Heterogeneous Environment
Robust Federated Learning in a Heterogeneous Environment
Avishek Ghosh
Justin Hong
Dong Yin
Kannan Ramchandran
OODFedML
58
217
0
16 Jun 2019
Towards Federated Learning at Scale: System Design
Towards Federated Learning at Scale: System Design
Keith Bonawitz
Hubert Eichner
W. Grieskamp
Dzmitry Huba
A. Ingerman
...
H. B. McMahan
Timon Van Overveldt
David Petrou
Daniel Ramage
Jason Roselander
FedML
121
2,666
0
04 Feb 2019
LEAF: A Benchmark for Federated Settings
LEAF: A Benchmark for Federated Settings
S. Caldas
Sai Meher Karthik Duddu
Peter Wu
Tian Li
Jakub Konecný
H. B. McMahan
Virginia Smith
Ameet Talwalkar
FedML
147
1,421
0
03 Dec 2018
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
406
17,486
0
17 Feb 2016
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