9 citations · 10 across the 6 of their papers we have counts for
6 papers
Unsupervised Dynamic Feature Selection for Robust Latent Spaces in Vision Tasks
Bruno Corcuera, Carlos Eiras-Franco, Brais Cancela
Latent representations are critical for the performance and robustness of machine learning models, as they encode the essential features of data in a compact and informative manner…
Predictively Combatting Toxicity in Health-related Online Discussions through Machine Learning
Jorge Paz-Ruza, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas +1
In health-related topics, user toxicity in online discussions frequently becomes a source of social conflict or promotion of dangerous, unscientific behaviour; common approaches fo…
Evaluate with the Inverse: Efficient Approximation of Latent Explanation Quality Distribution
Carlos Eiras-Franco, Anna Hedström, Marina M. -C. Höhne
Obtaining high-quality explanations of a model's output enables developers to identify and correct biases, align the system's behavior with human values, and ensure ethical complia…
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…
Sustainable transparency in Recommender Systems: Bayesian Ranking of Images for Explainability
Jorge Paz-Ruza, Amparo Alonso-Betanzos, Berta Guijarro-Berdiñas +2
Recommender Systems have become crucial in the modern world, commonly guiding users towards relevant content or products, and having a large influence over the decisions of users a…
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces
Iñigo López-Riobóo Botana, Carlos Eiras-Franco, Julio Hernandez-Castro +1
Most proposals in the anomaly detection field focus exclusively on the detection stage, specially in the recent deep learning approaches. While providing highly accurate prediction…