Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Clock-tuning has been classified as important but tough tasks due to the non-convex nature caused by the skew requirements. As a result, all existing mathematical programming appr...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as PCA, MDS, and SOM can be used to map high-dimensional data t...
Tobias Schreck, Tatiana von Landesberger, Sebastia...
In this paper, we present methods to analyze dialog coherence that help us to automatically distinguish between coherent and incoherent conversations. We build a machine learning ...