10 citations · 10 across the 4 of their papers we have counts for
10 papers
Meta-aprendizado para otimizacao de parametros de redes neurais
Tarsicio Lucas, Teresa Ludermir, Ricardo Prudencio +1
The optimization of Artificial Neural Networks (ANNs) is an important task to the success of using these models in real-world applications. The solutions adopted to this task are e…
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…
cf2vec: Collaborative Filtering algorithm selection using graph distributed representations
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
Algorithm selection using Metalearning aims to find mappings between problem characteristics (i.e. metafeatures) with relative algorithm performance to predict the best algorithm(s…
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…
Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
To select the best algorithm for a new problem is an expensive and difficult task. However, there are automatic solutions to address this problem: using Metalearning, which takes a…
CF4CF: Recommending Collaborative Filtering algorithms using Collaborative Filtering
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
Automatic solutions which enable the selection of the best algorithms for a new problem are commonly found in the literature. One research area which has recently received consider…