Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...
: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
: Current learning modelling languages do not allow formalization of scripts where generic tools are required. This limitation is especially relevant on remote courses when using c...
Abstract. We present an SVM-based learning algorithm for information extraction, including experiments on the influence of different algorithm settings. Our approach needs fewer ...