68 citations · 69 across the 4 of their papers we have counts for
4 papers
An Open Source Python Library for Anonymizing Sensitive Data
Judith Sáinz-Pardo Díaz, Álvaro López García
Open science is a fundamental pillar to promote scientific progress and collaboration, based on the principles of open data, open source and open access. However, the requirements…
Personalized Federated Learning for improving radar based precipitation nowcasting on heterogeneous areas
Judith Sáinz-Pardo Díaz, María Castrillo, Juraj Bartok +7
The increasing generation of data in different areas of life, such as the environment, highlights the need to explore new techniques for processing and exploiting data for useful p…
Comparison of machine learning models applied on anonymized data with different techniques
Judith Sáinz-Pardo Díaz, Álvaro López García
Anonymization techniques based on obfuscating the quasi-identifiers by means of value generalization hierarchies are widely used to achieve preset levels of privacy. To prevent dif…
Study of the performance and scalability of federated learning for medical imaging with intermittent clients
Judith Sáinz-Pardo Díaz, Álvaro López García
Federated learning is a data decentralization privacy-preserving technique used to perform machine or deep learning in a secure way. In this paper we present theoretical aspects ab…