We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
This paper studies the aggregation of predictions made by tree-based models for several perturbed versions of the attribute vector of a test case. A closed-form approximation of t...
In this paper, we present a controllable, fast and efficient particle system framework for skeletal implicit surfaces defined by the BlobTree model. We propose efficient algori...
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
The paper describes a concept for GIS based terrain mobility modelling and optimization of off-road route. The concept of generation of cost surface is based on machine, terrain, ...