Abstract. In practice, most computer intrusions begin by misusing programs in clever ways to obtain unauthorized higher levels of privilege. One e ective way to detect intrusive ac...
Anup K. Ghosh, Christoph C. Michael, Michael Schat...
Abstract. Machine learning approaches in natural language processing often require a large annotated corpus. We present a complementary approach that utilizes expert knowledge to o...
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
Different evaluation measures assess different characteristics of machine learning algorithms. The empirical evaluation of algorithms and classifiers is a matter of on-going debat...
Marina Sokolova, Nathalie Japkowicz, Stan Szpakowi...
In human mesenchymal stem cells the envelope surrounding the nucleus, as visualized by the nuclear lamina, has a round and flat shape. The lamina structure is considerably deformed...
Ofer M. Shir, Vered Raz, Roeland W. Dirks, Thomas ...
At Google, experimentation is practically a mantra; we evaluate almost every change that potentially affects what our users experience. Such changes include not only obvious user-...
Diane Tang, Ashish Agarwal, Deirdre O'Brien, Mike ...
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
This paper looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn ...