Nuria Rodríguez Barroso
Category
PhDContact
rbnuria@uJybqoKgr.es
Organization
UGR
| Total | From 2019: | |
|---|---|---|
| Citas | Total: 488 | From 2019: 488 |
| Índice H | Total: 7 | From 2019: 7 |
| Índice i10 | Total: 7 | From 2019: 7 |
Papers (14)
| Title | Authors | Year |
|---|---|---|
| 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 |
| RAB-DEF: Dynamic and explainable defense against adversarial attacks in Federated Learning to fair poor clients | N Rodríguez-Barroso, M Luzón, F Herrera. | 2024 |
| Interactive Telegram Bot as a Support Tool for Teaching in Higher Education | JL Suárez-Díaz, N Rodríguez-Barroso, G Gómez-Trenado. | 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 |
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