We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of ...
Constantinos Constantinopoulos, Michalis K. Titsia...
Abstract. We propose a variational model which permits to simultaneously deblur and oversample an image. Indeed, after some recalls on an existing variational model for image overs...
Present approaches to human face detection have made several assumptions that restrict their ability to be extended to general imaging conditions. We identify that the key factori...
We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of t...