: This paper introduces a tailored procedure model to construct reference models by using rich empirical data. The procedure model has been built based on requirements from the pub...
Abstract. Finite mixture models can be used in estimating complex, unknown probability distributions and also in clustering data. The parameters of the models form a complex repres...
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
In this paper we show how a segmentation as preprocessing paradigm can be used to improve the efficiency and accuracy of model search in an image. We operationalize this idea usin...
Domain specific languages (DSLs) play a cornerstone Model-Driven Software Development. The abstract syntax of a DSL is usually defined by a metamodel, while inplace model transf...