315 search results - page 15 / 63 » Structural Learning from Iconic Representations |
IJAR
2006
13 years 9 months ago
2006
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
NIPS
2007
13 years 11 months ago
2007
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
LATA
2010
Springer
14 years 4 months ago
2010
Springer
Abstract. Learnability is a vital property of formal grammars: representation classes should be defined in such a way that they are learnable. One way to build learnable represent...
CVPR
2007
IEEE
14 years 12 months ago
2007
IEEE
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
CVPR
2011
IEEE
13 years 7 months ago
2011
IEEE
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...