Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Artificial Neural Networks are universal and highly flexible function approximators first used in the fields of cognitive science and engineering. In recent years, Neural Networks...
In a public cloud, bandwidth is traditionally priced in a pay-asyou-go model. Reflecting the recent trend of augmenting cloud computing with bandwidth guarantees, we consider a n...
Background: Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing...
Shawn Cokus, Sherri Rose, David Haynor, Niels Gr&o...
We propose a trace fitting algorithm for Markovian Arrival Processes (MAPs) that can capture statistics of any order of interarrival times between measured events. By studying re...