: Network topology not only tells about tightly-connected “communities,” but also gives cues on more subtle properties of the vertices. We introduce a simple probabilistic late...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
We propose a method for learning models of people’s motion behaviors in an indoor environment. As people move through their environments, they do not move randomly. Instead, the...
The goal of the semantic web is to facilitate the exchange of meaningful information in a form that is easy for machines to process. The goal of an e-learning system is to support ...