The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Machine learning algorithms have recently attracted much interest for effective link adaptation due to their flexibility and ability to capture more environmental effects implicitl...
In the last few years the research community has proposed several techniques for network traffic classification. While the performance of these methods is promising especially for ...
Many computer vision algorithms such as object tracking and event detection assume that a background model of the scene under analysis is known. However, in many practical circums...