With the rapid development of information technology, many applications have to deal with potentially infinite data streams. In such a dynamic context, storing the whole data stre...
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
— A hormone-inspired task scheduling method is described which assigns tasks to a group of robots, taking into account the robots’ performances. This method draws on previous w...
Multiple-instance learning (MIL) is a generalization of the supervised learning problem where each training observation is a labeled bag of unlabeled instances. Several supervised ...
With the increasing use of large image and video archives and high-resolution multimedia data streams in many of today’s research and application areas, there is a growing need f...