Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
The study of networked systems is an emerging field, impacting almost every area of engineering and science, including the important domains of communication systems, biology, soc...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
The signal-dependent rank order mean (SD-ROM) ?lter is effective at removing high levels of impulse noise from 2D scalar-valued signals. Excellent results have been presented for ...
In this work, a novel probability distribution is proposed to model sparse directional data. The Directional Laplacian Distribution (DLD) is a hybrid between the linear Laplacian d...