The adaptive estimation of a time-varying parameter vector in a linear Gaussian model is considered where we a priori know that the parameter vector belongs to a known arbitrary s...
Technology mapping can be viewed as the optimization problem of finding a minimum cost cover of the given Boolean network by choosing from given library of logic cells. The core of...
Recognition of shapes in images is an important problem in computer vision with application in various medical problems, including robotic surgery and cell analysis. The similarit...
Imitation Learning, while applied successfully on many large real-world problems, is typically addressed as a standard supervised learning problem, where it is assumed the trainin...
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...