In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a ba...
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Learning the common structure shared by a set of supervised tasks is an important practical and theoretical problem. Knowledge of this structure may lead to better generalization ...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
This paper addresses the design of a large area, high resolution, networked pressure sensing floor with primary application in movement-based human-computer interaction (M-HCI). T...
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...