Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...
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 the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some fe...
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...