We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Embedded control systems are often implemented in small microprocessors enabled with real-time technology. In this context, control laws are often designed according to discrete-ti...
We introduce and analyze a deterministic fluid model that serves as an approximation for the Gt/GI/st + GI manyserver queueing model, which has a general time-varying arrival pro...
: Since the advent of Gnutella, Peer-to-Peer (P2P) protocols have matured towards a fundamental design element for large-scale, self-organising distributed systems. Many research e...
Abstract. Active Appearance Models (AAM) are compact representations of the shape and appearance of objects. Fitting AAMs to images is a difficult, non-linear optimization task. Tr...