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» Sparse Representation for Gaussian Process Models
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IJCAI
2007
13 years 9 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
ICA
2010
Springer
13 years 8 months ago
Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation
Two-photon calcium imaging is an emerging experimental technique that enables the study of information processing within neural circuits in vivo. While the spatial resolution of th...
Eva L. Dyer, Marco F. Duarte, Don H. Johnson, Rich...
ICIP
2003
IEEE
14 years 9 months ago
Image fusion with the Hermite transform
The Hermite Transform is an image representation model that incorporates some important properties of visual perception such as the analysis through overlapping receptive fields a...
A. Lopez-Caloca, Boris Escalante-Ramírez
ECCV
2006
Springer
14 years 9 months ago
Sparse Flexible Models of Local Features
Abstract. In recent years there has been growing interest in recognition models using local image features for applications ranging from long range motion matching to object class ...
Gustavo Carneiro, David Lowe
NEUROSCIENCE
2001
Springer
14 years 1 days ago
Neural Mechanisms for Representing Surface and Contour Features
Contours and surfaces are basic qualities which are processed by the visual system to aid the successful behavior of autonomous beings within the environment. There is increasing e...
Thorsten Hansen, Heiko Neumann