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ECCV
1994
Springer
14 years 22 days ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
CISS
2007
IEEE
14 years 18 days ago
Energy Efficient Routing for Statistical Inference of Markov Random Fields
The problem of routing of sensor observations for optimal detection of a Markov random field (MRF) at a designated fusion center is analyzed. Assuming that the correlation structur...
Animashree Anandkumar, Lang Tong, Ananthram Swami
ACL
2008
13 years 10 months ago
Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums
Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not on...
Shilin Ding, Gao Cong, Chin-Yew Lin, Xiaoyan Zhu
COLING
2008
13 years 10 months ago
Training Conditional Random Fields Using Incomplete Annotations
We address corpus building situations, where complete annotations to the whole corpus is time consuming and unrealistic. Thus, annotation is done only on crucial part of sentences...
Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hirok...
COLING
2008
13 years 10 months ago
Word Sense Disambiguation for All Words using Tree-Structured Conditional Random Fields
We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
Jun Hatori, Yusuke Miyao, Jun-ichi Tsujii