Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Due to the increasing complexity, the behavior of large-scale distributed systems becomes difficult to predict. The ability of on-line identification and autotuning of adaptive co...
Although evolutionary algorithms (EAs) are widely used in practical optimization, their theoretical analysis is still in its infancy. Up to now results on the (expected) runtime ar...
This paper investigates a distributed and adaptive approach to manage spectrum usage in dynamic spectrum access networks. While previous works focus on centralized provisioning, w...
This paper presents an adaptive technique to animate deformable bodies in real-time. In contrast to most previous work, we introduce a multi-resolution model that locally refines...