It is often highly valuable for organizations to have their data analyzed by external agents. However, any program that computes on potentially sensitive data risks leaking inform...
We address the problem of linking observations from reality to a semantic web based knowledge base. Concepts in the biological domain are increasingly being formalized through ont...
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...