Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
In most advanced real-time control applications such as service robots, the tasks have different criticality, flexible timing constraints and variable execution time. For instance...
Model-driven software product lines are an emerging topic in research and industry, as they promise higher development speed and easier adaptability to customer needs. The generat...
Christoph Elsner, Daniel Lohmann, Wolfgang Schr&ou...
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Bluetooth is a new technology for Wireless Personal Area Networks (WPANs). It intends to eliminate the need of wires and connectors between a variety of devices, like PCs and thei...