A model capturing the data manipulation capabilities of a large class of methods in ohjectoriented databases is proposed and investsigated. The model uses a deterministic, paralle...
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
Feature modeling is a notation and an approach for modeling commonality and variability in product families. In their basic form, feature models contain mandatory/optional feature...
In the field of controlled release technology for pesticides or active ingredients (AI), models that can predict its delivery during application are important for purposes of desi...
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...