A probabilistic learning model for vague queries and missing or imprecise information in databases is described. Instead of retrieving only a set of answers, our approach yields a...
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
In this paper we present lessons learned in the Evaluating Predictive Uncertainty Challenge. We describe the methods we used in regression challenges, including our winning method ...
The Named Entity Recognition (NER) task has been garnering significant attention in NLP as it helps improve the performance of many natural language processing applications. In th...
We consider the problem of anomaly detection in multiple co-evolving data streams. In this paper, we introduce FRAHST (Fast Rank-Adaptive row-Householder Subspace Tracking). It au...
Pedro Henriques dos Santos Teixeira, Ruy Luiz Mili...