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ORCIDJudith Sáinz-Pardo Díaz
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2020 – today
- 2025
[j4]Giang Thu Nguyen
, Judith Sáinz-Pardo Díaz, Amanda Calatrava, Lisana Berberi, Oleksandr Lytvyn, Valentin Kozlov, Viet D. Tran, Germán Moltó, Álvaro López García:
Landscape of machine learning evolution: privacy-preserving federated learning frameworks and tools. Artif. Intell. Rev. 58(2): 51 (2025)- [j3]Lisana Berberi, Valentin Kozlov, Giang Nguyen, Judith Sáinz-Pardo Díaz, Amanda Calatrava, Germán Moltó, Viet D. Tran, Álvaro López García:
Machine learning operations landscape: platforms and tools. Artif. Intell. Rev. 58(6): 167 (2025) - [c3]Leonhard Duda, Khadijeh Alibabaei, Elena Vollmer, Leon Klug, Valentin Kozlov, Lisana Berberi, Mishal Benz, Rebekka Volk, Juan Pedro Gutiérrez H. Muriedas, Markus Götz, Judith Sáinz-Pardo Díaz, Álvaro López García, Frank Schultmann, Achim Streit:
Exploring Federated Learning for Thermal Urban Feature Segmentation - A Comparison of Centralized and Decentralized Approaches. ICCSA (1) 2025: 285-302 - [i8]Judith Sáinz-Pardo Díaz, Álvaro López García:
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data. CoRR abs/2501.15949 (2025) - [i7]Judith Sáinz-Pardo Díaz, Andreas Athanasiou, Kangsoo Jung, Catuscia Palamidessi, Álvaro López García:
Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks. CoRR abs/2502.01352 (2025) - 2024
- [j2]Judith Sáinz-Pardo Díaz, María Castrillo, Juraj Bartok, Ignacio Heredia Cacha, Irina Malkin Ondík, Ivan Martynovskyi, Khadijeh Alibabaei, Lisana Berberi, Valentin Kozlov, Álvaro López García:
Personalized federated learning for improving radar based precipitation nowcasting on heterogeneous areas. Earth Sci. Informatics 17(6): 5561-5584 (2024) - [c2]Judith Sáinz-Pardo Díaz, Andrés Heredia Canales, Ignacio Heredia Cacha, Viet D. Tran, Giang T. Nguyen, Khadijeh Alibabaei, Marta Obregón Ruiz, Susana Rebolledo Ruiz, Álvaro López García:
Making Federated Learning Accessible to Scientists: The AI4EOSC Approach. IH&MMSec 2024: 253-264 - [i6]Judith Sáinz-Pardo Díaz, María Castrillo, Juraj Bartok, Ignacio Heredia Cacha, Irina Malkin Ondík, Ivan Martynovskyi, Khadijeh Alibabaei, Lisana Berberi, Valentin Kozlov, Álvaro López García:
Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas. CoRR abs/2408.05761 (2024) - [i5]Judith Sáinz-Pardo Díaz, Álvaro López García:
An Open Source Python Library for Anonymizing Sensitive Data. CoRR abs/2408.10766 (2024) - 2023
- [j1]Judith Sáinz-Pardo Díaz, Álvaro López García:
Study of the performance and scalability of federated learning for medical imaging with intermittent clients. Neurocomputing 518: 142-154 (2023) - [c1]Judith Sáinz-Pardo Díaz, Álvaro López García:
Comparison of machine learning models applied on anonymized data with different techniques. CSR 2023: 618-623 - [i4]Judith Sáinz-Pardo Díaz, Álvaro López García:
Comparison of machine learning models applied on anonymized data with different techniques. CoRR abs/2305.07415 (2023) - 2022
- [i3]Ignacio Heredia Cacha, Judith Sáinz-Pardo Díaz, María Castrillo Melguizo, Álvaro López García:
Forecasting COVID-19 spreading trough an ensemble of classical and machine learning models: Spain's case study. CoRR abs/2207.05753 (2022) - [i2]Judith Sáinz-Pardo Díaz, Álvaro López García:
Study of the performance and scalability of federated learning for medical imaging with intermittent clients. CoRR abs/2207.08581 (2022) - [i1]Judith Sáinz-Pardo Díaz, Álvaro López García:
pyCANON: A Python library to check the level of anonymity of a dataset. CoRR abs/2208.07556 (2022)
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