Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...
— To proactively defend against intruders from readily jeopardizing single-path data sessions, we propose a distributed secure multipath solution to route data across multiple pa...
Network based intruders seldom attack directly from their own hosts, but rather stage their attacks through intermediate “stepping stones” to conceal their identity and origin...