We propose a novel approach for statistical risk modeling of network attacks that lets an operator perform risk analysis using a data model and an impact model on top of an attack ...
We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the point...
We present a generative model for determining the information content of a message without analyzing the message content. Such a tool is useful for automated analysis of the vast ...
Yingjie Zhou, Malik Magdon-Ismail, William A. Wall...
Abstract In this survey, the currently available ultrawideband-based non-line-of-sight (NLOS) identification and error mitigation methods are presented. They are classified into se...
Jasurbek Khodjaev, Yongwan Park, Aamir Saeed Malik
For a large class of applications, there is time to train the system. In this paper, we propose a learning-based approach to patch perspective rectification, and show that it is b...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...