Abstract. Combining statistical and relational learning receives currently a lot of attention. The majority of statistical relational learning approaches focus on density estimatio...
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Synchronous data-flow languages such as Scade/Lustre manage infinite sequences, or streams, as primitive values making them naturally adapted to the description of datadominated s...
IDS research still needs to strengthen mathematical foundations and theoretic guidelines. In this paper, we build a formal framework, based on information theory, for analyzing and...
Guofei Gu, Prahlad Fogla, David Dagon, Wenke Lee, ...