Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
In this paper we present concepts for and experiences with a Situated Public Display system deployed in a university setting. We identify the rate with which information is updated...
This paper deals with the adaptive variance scaling issue in continuous Estimation of Distribution Algorithms. A phenomenon is discovered that current adaptive variance scaling me...
We present in this paper the recent developments done in P2P-MPI, a grid middleware, concerning the fault management, which covers fault-tolerance for applications and fault detect...
In this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam fi...