This paper explains how efficient support for semiregular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work ...
The coarse-grained reconfigurable architecture ADRES (Architecture for Dynamically Reconfigurable Embedded Systems) and its compiler offer high instruction-level parallelism (ILP)...
Kehuai Wu, Andreas Kanstein, Jan Madsen, Mladen Be...
We propose a neural network based autoassociative memory system for unsupervised learning. This system is intended to be an example of how a general information processing architec...
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...