3 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Clust-PSI-PFL: A Population Stability Index Approach for Clustered Non-IID Personalized Federated Learning
Daniel M. Jimenez-Gutierrez, Mehrdad Hassanzadeh, David Solans +5
Federated learning (FL) supports privacy-preserving, decentralized machine learning (ML) model training by keeping data on client devices. However, non-independent and identically…
PSI-PFL: Population Stability Index for Client Selection in non-IID Personalized Federated Learning
Daniel-M. Jimenez-Gutierrez, David Solans, Mohammed Elbamby +1
Federated Learning (FL) enables decentralized machine learning (ML) model training while preserving data privacy by keeping data localized across clients. However, non-independent…
A Thorough Assessment of the Non-IID Data Impact in Federated Learning
Daniel M. Jimenez-Gutierrez, Mehrdad Hassanzadeh, Aris Anagnostopoulos +2
Federated learning (FL) allows collaborative machine learning (ML) model training among decentralized clients' information, ensuring data privacy. The decentralized nature of FL de…
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions
Daniel M. Jimenez G., David Solans, Mikko Heikkila +4
Recent advances in machine learning have highlighted Federated Learning (FL) as a promising approach that enables multiple distributed users (so-called clients) to collectively tra…