This paper studies the input design problem for system identification where time domain constraints have to be considered. A finite Markov chain is used to model the input of the s...
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
This paper demonstrates how machine learning methods can be applied to deal with a realworld decipherment problem where very little background knowledge is available. The goal is ...
We describe and analyze sparse graphical code constructions for the problems of source coding with decoder side information (the Wyner-Ziv problem), and channel coding with encoder...
: Automatic model construction is a core problem in mobile robotics. To solve this task efficiently, we need a motion strategy to guide a robot equipped with a range sensor through...