Abstract This paper presents an approach to designing and implementing extensible computational models for perceiving systems based on a knowledge-driven joint inference approach. ...
Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
—This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain o...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...