We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...
During face-to-face conversation, the speaker’s head is continually in motion. These movements serve a variety of important communicative functions. Our goal is to develop a mod...
This report presents a model-driven, stress test methodology aimed at increasing chances of discovering faults related to network traffic in Distributed Real-Time Systems (DRTS). T...
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...