The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
Aspect extraction is a central problem in sentiment analysis. Current methods either extract aspects without categorizing them, or extract and categorize them using unsupervised t...
We propose a robust scene recognition framework using scene context information for multimedia contents. Multimedia contents consist of scene sequences that are more likely to hap...
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...