The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
This paper presents a system for visualizing mobile object frameworks. In such frameworks, the objects can migrate to remote hosts, along with their state and behavior, while the ...
The arrival process of jobs submitted to a parallel system is bursty, leading to fluctuations in the load at many time scales. In particular, rare events of extreme load may occu...