A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
— We present a general approach for the hierarchical segmentation and labeling of document layout structures. This approach models document layout as a grammar and performs a glo...