This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
We present a novel framework for tracking of a long sequence of human activities, including the time instances of change from one activity to the next, using a closed-loop, non-li...
— High variability of access resources in heterogenous wireless networks and limited computing power and battery life of mobile computing devices such as smartphones call for nov...
Dimitrios Tsamis, Tansu Alpcan, Jatinder Pal Singh...
— Bayesian networks play a key role in decision support within health care. Physicians rely on Bayesian networks to give medical treatment, generate what-if scenarios, and other ...