9 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
Robust gene prioritization for Dietary Restriction via Fast-mRMR Feature Selection techniques
Rubén Fernández-Farelo, Jorge Paz-Ruza, Bertha Guijarro-Berdiñas +2
Gene prioritization (identifying genes potentially associated with a biological process) is increasingly tackled with Artificial Intelligence. However, existing methods struggle wi…
A robust methodology for long-term sustainability evaluation of Machine Learning models
Jorge Paz-Ruza, João Gama, Amparo Alonso-Betanzos +1
Sustainability and efficiency have become essential considerations in the development and deployment of Artificial Intelligence systems, but existing regulatory practices for Green…
Sustainable techniques to improve Data Quality for training image-based explanatory models for Recommender Systems
Jorge Paz-Ruza, David Esteban-Martínez, Amparo Alonso-Betanzos +1
Visual explanations based on user-uploaded images are an effective and self-contained approach to provide transparency to Recommender Systems (RS), but intrinsic limitations of dat…
Positive-Unlabelled Learning for identifying new candidate Dietary Restriction-related genes among Ageing-related genes
Jorge Paz-Ruza, Alex A. Freitas, Amparo Alonso-Betanzos +1
Dietary Restriction (DR) is one of the most popular anti-ageing interventions; recently, Machine Learning (ML) has been explored to identify potential DR-related genes among ageing…
Beyond RMSE and MAE: Introducing EAUC to unmask hidden bias and unfairness in dyadic regression models
Jorge Paz-Ruza, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas +2
Dyadic regression models, which output real-valued predictions for pairs of entities, are fundamental in many domains (e.g. obtaining user-product ratings in Recommender Systems) a…