The problem of choosing a good parameter setting for a better generalization performance in a learning task is the so-called model selection. A nested uniform design (UD) methodol...
Chien-Ming Huang, Yuh-Jye Lee, Dennis K. J. Lin, S...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
The one-class and cost-sensitive support vector machines (SVMs) are state-of-the-art machine learning methods for estimating density level sets and solving weighted classificatio...
This paper describes results concerning the robustness and generalization capabilities of kernel methods in detecting coordinated distributed multiple attacks (CDMA) using network...
Srinivas Mukkamala, Krishna Yendrapalli, Ram B. Ba...
Telephony over IP is exposed to multiple security threats. Conventional protection mechanisms do not fit into the highly dynamic, open and large-scale settings of VoIP infrastructu...