- Events are at the core of reactive applications, which have become popular in many domains. Contemporary modeling tools lack the capability express the event semantics and relati...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
This paper deals with the analysis of temporal dependence in multivariate highfrequency time series data. The dependence structure between the marginal series is modelled through ...
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...