In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine ...
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...