827 search results - page 131 / 166 » Variational methods for Reinforcement Learning |
SIAMIS
2010
13 years 2 months ago
2010
This article proposes a new method for image separation into a linear combination of morphological components. Sparsity in fixed dictionaries is used to extract the cartoon and osc...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
WMCSA
2008
IEEE
14 years 2 months ago
2008
IEEE
Remote patient monitoring generates much more data than healthcare professionals are able to manually interpret. Automated detection of events of interest is therefore critical so...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...