Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
We present two solutions for the scale selection problem in computer vision. The rst one is completely nonparametric and is based on the the adaptive estimation of the normalized ...
Background: There has been recent concern regarding the inability of predictive modeling approaches to generalize to new data. Some of the problems can be attributed to improper m...
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...