A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...
Mining for outliers in sequential databases is crucial to forward appropriate analysis of data. Therefore, many approaches for the discovery of such anomalies have been proposed. ...
This work provides a generalization of the traditional response surface methodology (RSM) that can be applied to complex, multi-objective simulation studies. These problems involv...
Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for Web ranking algorithms. In fact, there are sti...
Bruno M. Fonseca, Paulo Braz Golgher, Bruno P&ocir...
In geospatial applications with heterogeneous classification schemes that describe related domains, an ontology-driven approach to data sharing and interoperability relies on the ...