Due to the increasing abstraction gap between the initial system model and a final implementation, the verification of the respective models against each other is a formidable task...
This paper studies a novel paradigm for learning formal languages from positive and negative examples which consists of mapping strings to an appropriate highdimensional feature s...
Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g. statistical data analysis and information-theoretic image registration. ...
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...