20 citations · 71 across the 13 of their papers we have counts for
4 papers · 1 filter
Systematic analysis of the impact of label noise correction on ML Fairness
I. Oliveira e Silva, C. Soares, I. Sousa +1
Arbitrary, inconsistent, or faulty decision-making raises serious concerns, and preventing unfair models is an increasingly important challenge in Machine Learning. Data often refl…
Preference rules for label ranking: Mining patterns in multi-target relations
Cláudio Rebelo de Sá, Paulo Azevedo, Carlos Soares +2
In this paper we investigate two variants of association rules for preference data, Label Ranking Association Rules and Pairwise Association Rules. Label Ranking Association Rules…
Characterizing classification datasets: a study of meta-features for meta-learning
Adriano Rivolli, Luís P. F. Garcia, Carlos Soares +2
Meta-learning is increasingly used to support the recommendation of machine learning algorithms and their configurations. Such recommendations are made based on meta-data, consisti…
Using Contextual Information as Virtual Items on Top-N Recommender Systems
Marcos A. Domingues, Alipio Mario Jorge, Carlos Soares
Traditionally, recommender systems for the Web deal with applications that have two dimensions, users and items. Based on access logs that relate these dimensions, a recommendation…