338 search results - page 52 / 68 » Learning Flexible Features for Conditional Random Fields |
166
Voted
FOIKS
2008
Springer
15 years 11 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
118
Voted
CVPR
2007
IEEE
16 years 4 months ago
2007
IEEE
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
127
Voted
ECCV
2006
Springer
16 years 4 months ago
2006
Springer
Abstract. Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, rec...
119
Voted
NIPS
2007
15 years 4 months ago
2007
We present a new and efficient semi-supervised training method for parameter estimation and feature selection in conditional random fields (CRFs). In real-world applications suc...
136
Voted
CIKM
2008
Springer
15 years 4 months ago
2008
Springer
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...