3 papers
cs.CL2026
"OK Aura, Be Fair With Me": Demographics-Agnostic Training for Bias Mitigation in Wake-up Word Detection
Fernando López, Paula Delgado-Santos, Pablo Gómez +2
Voice-based interfaces are widely used; however, achieving fair Wake-up Word detection across diverse speaker populations remains a critical challenge due to persistent demographic…
cs.LG2025
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…
cs.LG2024
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…