Recognizing and analyzing change is an important human virtue because it enables us to anticipate future scenarios and thus allows us to act pro-actively. One approach to understa...
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
We address the problem of capturing and tracking local correlations among time evolving time series. Our approach is based on comparing the local auto-covariance matrices (via the...
In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions for a procedural and ill-defined domain wher...
Philippe Fournier-Viger, Roger Nkambou, Engelbert ...