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CVPR
2008
IEEE
16 years 5 months ago
Learning human actions via information maximization
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...
Jingen Liu, Mubarak Shah
IJAR
2006
89views more  IJAR 2006»
15 years 3 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
NIPS
2007
15 years 4 months ago
A Spectral Regularization Framework for Multi-Task Structure Learning
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...
EUROSSC
2007
Springer
15 years 9 months ago
The Design of a Pressure Sensing Floor for Movement-Based Human Computer Interaction
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...
Sankar Rangarajan, Assegid Kidané, Gang Qia...
ECCV
2006
Springer
16 years 4 months ago
Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion
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...
Dahua Lin, Xiaoou Tang