9 citations · 10 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…