We propose a modification of the dynamic neural field model of Amari [1], aiming at reducing the simulation effort by employing spaceand frequency representations of the dynamic st...
Alexander Gepperth, Jannik Fritsch, Christian Goer...
Modern network processor systems require the ability to adapt their processing capabilities at runtime to changes in network traffic. Traditionally, network processor applications ...
A number of new network storage architectures have emerged recently that provide shared, adaptable and high-performance storage systems for dataintensive applications. Three commo...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
With the current trend toward multicore architectures, improved execution performance can no longer be obtained via traditional single-thread instruction level parallelism (ILP), ...