Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
—Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to...
Andreas Fidjeland, Etienne B. Roesch, Murray Shana...
We present a stereo algorithm that achieves high quality results while maintaining real-time performance. The key idea is simple: we introduce an adaptive aggregation step in a dy...
The automatic integration of devices into dynamic, automatically configured networks alone does not take advantage of the entire potential of Service Oriented Architectures (SOA)...
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...