194 search results - page 7 / 39 » Learning whom to trust: using graphical models for learning ... |
AAAI
2011
12 years 7 months ago
2011
We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...
CHI
2009
ACM
14 years 8 months ago
2009
ACM
Context-aware intelligent systems employ implicit inputs, and make decisions based on complex rules and machine learning models that are rarely clear to users. Such lack of system...
JMLR
2012
11 years 9 months ago
2012
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
SODA
2001
ACM
13 years 8 months ago
2001
ACM
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...