8 papers
GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning
Daniel M. Jimenez-Gutierrez, Albenzio Cirillo, Raffaele Nicolussi +2
We present GuidaPA, a privacy-preserving chatbot for the Italian Public Administration (PA) trained via Federated Learning (FL) on documentation from two national PA platforms, SIG…
Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
Daniel M. Jimenez-Gutierrez, Dario Pighin, Enrique Zuazua +4
Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL: Horizontal FL (HFL), where al…
FedLECC: Cluster- and Loss-Guided Client Selection for Federated Learning under Non-IID Data
Daniel M. Jimenez-Gutierrez, Giovanni Giunta, Mehrdad Hassanzadeh +3
Federated Learning (FL) enables distributed Artificial Intelligence (AI) across cloud-edge environments by allowing collaborative model training without centralizing data. In cross…
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…
On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions
Daniel M. Jimenez-Gutierrez, Yelizaveta Falkouskaya, Jose L. Hernandez-Ramos +3
Federated Learning (FL) is an emerging distributed machine learning paradigm enabling multiple clients to train a global model collaboratively without sharing their raw data. While…
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…