Irina Arévalo

According to our database, Irina Arévalo authored at least 9 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Spectral biclustering-driven scalability for post-hoc explainability in recommender systems.

Jose L. Salmeron, Irina Arévalo

Knowl. Based Syst., 2026

CAFP: A post-processing framework for group fairness via counterfactual model averaging.

Irina Arévalo, Marcos Oliva

Knowl. Based Syst., 2026

Model-agnostic post-hoc explainability for recommender systems.

Irina Arévalo, Jose L. Salmeron

Expert Syst. Appl., 2026

2025

Concurrent vertical and horizontal federated learning with fuzzy cognitive maps.

Jose L. Salmeron, Irina Arévalo

Future Gener. Comput. Syst., 2025

2024

Blind Federated Learning without initial model.

Jose L. Salmeron, Irina Arévalo

J. Big Data, December, 2024

A Chaotic Maps-Based Privacy-Preserving Distributed Deep Learning for Incomplete and Non-IID Datasets.

Irina Arévalo, Jose L. Salmeron

IEEE Trans. Emerg. Top. Comput., 2024

Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data.

Jose L. Salmeron, Irina Arévalo, Antonio Ruiz-Celma

CoRR, 2024

Privacy-preserving distributed learning with chaotic maps.

Irina Arévalo, Jose L. Salmeron, Ivan Romero

Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent Systems, 2024

2020

A Privacy-Preserving, Distributed and Cooperative FCM-Based Learning Approach for Cancer Research.

Jose L. Salmeron, Irina Arévalo

Proceedings of the Rough Sets - International Joint Conference, 2020