The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
The goal of this paper is to investigate the impact of dictionary choosing for a total variation dictionary model. After theoretical analysis, we present the experiments in which ...
Since electronic and open environments became a reality, computational trust and reputation models have attracted increasing interest in the field of multiagent systems (MAS). Some...
We present a random field based model for stereo vision with explicit occlusion labeling in a probabilistic framework. The model employs non-parametric cost functions that can be ...
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...