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FederatedTrust: A Solution for Trustworthy Federated Learning
v1v2 (latest)

FederatedTrust: A Solution for Trustworthy Federated Learning

Future generations computer systems (FGCS), 2023
20 February 2023
Pedro Miguel Sánchez Sánchez
Alberto Huertas Celdrán
Ning Xie
Gérome Bovet
Gregorio Martínez Pérez
Burkhard Stiller
ArXiv (abs)PDFHTMLGithub

Papers citing "FederatedTrust: A Solution for Trustworthy Federated Learning"

7 / 7 papers shown
Large Language Model Federated Learning with Blockchain and Unlearning
  for Cross-Organizational Collaboration
Large Language Model Federated Learning with Blockchain and Unlearning for Cross-Organizational Collaboration
Xuhan Zuo
Minghao Wang
Tianqing Zhu
Shui Yu
Wanlei Zhou
MU
305
4
0
18 Dec 2024
Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the
  Gap Between Interpretability and Robustness
Enabling Trustworthy Federated Learning in Industrial IoT: Bridging the Gap Between Interpretability and RobustnessIEEE Internet of Things Magazine (IEEE IoT Magazine), 2024
Senthil Kumar Jagatheesaperumal
Mohamed Rahouti
Ali Alfatemi
Nasir Ghani
V. K. Quy
Abdellah Chehri
AI4CE
224
19
0
01 Sep 2024
DART: A Solution for Decentralized Federated Learning Model Robustness
  Analysis
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis
Chao Feng
Alberto Huertas Celdrán
Jan von der Assen
Enrique Tomás Martínez Beltrán
Gérome Bovet
Burkhard Stiller
OODAAML
265
19
0
11 Jul 2024
Federated Learning and AI Regulation in the European Union: Who is
  Responsible? -- An Interdisciplinary Analysis
Federated Learning and AI Regulation in the European Union: Who is Responsible? -- An Interdisciplinary Analysis
Herbert Woisetschläger
Simon Mertel
Christoph Krönke
R. Mayer
Hans-Arno Jacobsen
FedML
369
4
0
11 Jul 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
Data Quality in Edge Machine Learning: A State-of-the-Art Survey
M. D. Belgoumri
Mohamed Reda Bouadjenek
Sunil Aryal
Hakim Hacid
434
2
0
01 Jun 2024
Sentinel: An Aggregation Function to Secure Decentralized Federated
  Learning
Sentinel: An Aggregation Function to Secure Decentralized Federated LearningEuropean Conference on Artificial Intelligence (ECAI), 2023
Chao Feng
Alberto Huertas Celdrán
Janosch Baltensperger
Enrique Tomás Martínez Beltrán
Gérome Bovet
Burkhard Stiller
300
8
0
12 Oct 2023
Decentralized Federated Learning: Fundamentals, State of the Art,
  Frameworks, Trends, and Challenges
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and ChallengesIEEE Communications Surveys and Tutorials (COMST), 2022
Enrique Tomás Martínez Beltrán
Mario Quiles Pérez
Pedro Miguel Sánchez Sánchez
Sergio López Bernal
Gérome Bovet
M. Pérez
Gregorio Martínez Pérez
Alberto Huertas Celdrán
FedML
601
471
0
15 Nov 2022
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