An adaptive user interface relies, to a large extent, upon an adequate user model (e.g., a representationof user-expertise). However, building a user model may be a tedious and ti...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
We study the problemof statisticallycorrect inference in networks whose basic representations are population codes. Population codes are ubiquitous in the brain, and involve the s...
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complex...