The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
In this work we develop an approach for anomaly detection for large scale networks such as that of an enterprize or an ISP. The traffic patterns we focus on for analysis are that...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
In this paper we provide a study about crime scenes and its features used in criminal investigations. We argue that the crime scene provides a large set of features that can be us...
Ricardo O. Abu Hana, Cinthia Obladen de Almendra F...