We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Many mathematical models involve flow equations characterized by nonconstant viscosity, and a Stokes type problem with variable viscosity coefficient arises. Appropriate block diag...
We propose a driver risk evaluation method based on the analysis of driving data captured with drive recorders. To evaluate the acceleration behavior of each driver we plot the ma...
Online forums are becoming a popular resource in the state of the art question answering (QA) systems. Because of its nature as an online community, it contains more updated knowl...