Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
Zero-days attacks are one of the most dangerous threats against computer networks. These, by definition, are attacks never seen before. Thus, defense tools based on a database of ...
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Background: The main goal of the PROMISE repository is to enable reproducible, and thus verifiable or refutable research. Over time, plenty of data sets became available, especial...
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...