222 search results - page 24 / 45 » Learning Optimal Parameters in Decision-Theoretic Rough Sets |
GECCO
2009
Springer
14 years 1 months ago
2009
Springer
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
GECCO
2006
Springer
14 years 8 days ago
2006
Springer
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
CCIA
2005
Springer
14 years 2 months ago
2005
Springer
IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detecti...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
NIPS
2008
13 years 10 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...