236 search results - page 13 / 48 » Learning How to Propagate Using Random Probing |
FOCS
1999
IEEE
14 years 1 days ago
1999
IEEE
We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
NAACL
2007
13 years 9 months ago
2007
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...