Many Ubiquitous computing applications can be considered as planning and acting problems in environments characterised by uncertainty and partial observability. Such systems rely ...
Existing content-based publish/subscribe systems are designed assuming that all matching publications are equally relevant to a subscription. As we cannot know in advance the dist...
Kresimir Pripuzic, Ivana Podnar Zarko, Karl Aberer
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Abstract. We present an approach to inferring probabilistic models of generegulatory networks that is intended to provide a more mechanistic representation of transcriptional regul...
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...