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» A Preference Model for Structured Supervised Learning Tasks
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ICDM
2005
IEEE
134views Data Mining» more  ICDM 2005»
13 years 10 months ago
A Preference Model for Structured Supervised Learning Tasks
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, su...
Fabio Aiolli
ACL
2012
11 years 7 months ago
Automatic Event Extraction with Structured Preference Modeling
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
Wei Lu, Dan Roth
CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 5 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
ACL
2009
13 years 2 months ago
Multi-Task Transfer Learning for Weakly-Supervised Relation Extraction
Creating labeled training data for relation extraction is expensive. In this paper, we study relation extraction in a special weakly-supervised setting when we have only a few see...
Jing Jiang
EMNLP
2010
13 years 3 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira