A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends |
MV Luzón, N Rodríguez-Barroso, A Argente-Garrido, D Jiménez-López, .... |
2024 |
FLEX: FLEXible Federated Learning Framework |
F Herrera, D Jiménez-López, A Argente-Garrido, N Rodríguez-Barroso, .... |
2024 |
Federated Learning for Exploiting Annotators’ Disagreements in Natural Language Processing |
N Rodríguez-Barroso, EM Cámara, JC Collados, MV Luzón, F Herrera. |
2024 |
Bot de Telegram interactivo como herramienta de apoyo para la enseñanza |
JL Suárez-Díaz, N Rodríguez-Barroso, G Gómez-Trenado. |
2024 |
Adversarial attacks and defences in Federated Learning |
N Rodríguez Barroso. |
2024 |
Defense Strategy against Byzantine Attacks in Federated Machine Learning: Developments towards Explainability |
N Rodríguez-Barroso, J Del Ser, MV Luzón, F Herrera. |
2024 |
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges |
N Rodríguez-Barroso, DJ López, M Luzón, F Herrera, E Martínez-Cámara. |
2022 |
Backdoor attacks-resilient aggregation based on Robust Filtering of Outliers in federated learning for image classification |
N Rodríguez-Barroso, E Martínez-Cámara, MV Luzón, F Herrera. |
2022 |
Federated Learning and Differential Privacy: Software tools analysis, the Sherpa. ai FL framework and methodological guidelines for preserving data privacy |
N Rodríguez-Barroso, G Stipcich, D Jiménez-López, JA Ruiz-Millán, .... |
2020 |
Dynamic Federated Learning Model for Identifying Adversarial Clients |
N Rodríguez-Barroso, E Martínez-Cámara, M Luzón, GG Seco, .... |
2020 |
Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning |
N Rodríguez-Barroso, E Martínez-Cámara, M Luzón, F Herrera. |
2020 |
Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms |
N Rodríguez-Barroso, AR Moya, JA Fernández, E Romero, .... |
2019 |