Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
We introduce into the classical Perceptron algorithm with margin a mechanism of unlearning which in the course of the regular update allows for a reduction of possible contributio...
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM...