We suggest to apply the hybrid neural network based on multi layer perceptron (MLP) and adaptive resonance theory (ART-2) for solving of navigation task of mobile robots. This appr...
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
We present some novel machine learning techniques for the identification of subcategorization information for verbs in Czech. We compare three different statistical techniques app...
The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can o...
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...