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» MINLIP: Efficient Learning of Transformation Models
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ATAL
2008
Springer
14 years 11 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
TMM
2008
167views more  TMM 2008»
14 years 9 months ago
Mining Appearance Models Directly From Compressed Video
In this paper, we propose an approach to learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in vide...
Datong Chen, Qiang Liu, Mingui Sun, Jie Yang
ECIS
2000
14 years 11 months ago
The Learning Administration - Shaping Change and Taking Off into the Future
- E-services will change the future of business as well as private relationships. The rearrangement of value chains, new competitive arenas and the growing necessity and interest i...
Hans-Jörg Bullinger, Werner Brettreich-Teichm...
CVPR
2003
IEEE
15 years 11 months ago
Representation and Detection of Deformable Shapes
We describe some techniques that can be used to represent and detect deformable shapes in images. The main difficulty with deformable template models is the very large or infinite...
Pedro F. Felzenszwalb
ICCV
2007
IEEE
15 years 11 months ago
Embedded Profile Hidden Markov Models for Shape Analysis
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas