Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Ma...
Claudine Badue, Felipe Pedroni, Alberto Ferreira d...
This conceptual paper outlines best practice use cases and standards for learning delivery that are the result of a European-wide best practice case study survey within the EU-fun...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...