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» Better Informed Training of Latent Syntactic Features
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CVPR
2011
IEEE
13 years 5 months ago
Learning Better Image Representations Using 'Flobject Analysis'
Unsupervised learning can be used to extract image representations that are useful for various and diverse vision tasks. After noticing that most biological vision systems for int...
Inmar Givoni, Patrick Li, Brendan Frey
CIKM
2008
Springer
13 years 9 months ago
The role of syntactic features in protein interaction extraction
Most approaches for protein interaction mining from biomedical texts use both lexical and syntactic features. However, the individual impact of these two kinds of features on the ...
Timur Fayruzov, Martine De Cock, Chris Cornelis, V...
LBM
2007
13 years 8 months ago
Syntactic Features for Protein-Protein Interaction Extraction
Background: Extracting Protein-Protein Interactions (PPI) from research papers is a way of translating information from English to the language used by the databases that store th...
Rune Sætre, Kenji Sagae, Jun-ichi Tsujii
ACL
2007
13 years 9 months ago
A Discriminative Syntactic Word Order Model for Machine Translation
We present a global discriminative statistical word order model for machine translation. Our model combines syntactic movement and surface movement information, and is discriminat...
Pi-Chuan Chang, Kristina Toutanova
ICIP
2006
IEEE
14 years 9 months ago
Unsupervised Image Layout Extraction
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...
David Liu, Datong Chen, Tsuhan Chen