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» Learning to Align: A Statistical Approach
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EMNLP
2009
13 years 3 months ago
Weighted Alignment Matrices for Statistical Machine Translation
Current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. They are prone to learn noisy rules due to alignment...
Yang Liu, Tian Xia, Xinyan Xiao, Qun Liu
PAMI
2006
178views more  PAMI 2006»
13 years 5 months ago
Learning Nonlinear Image Manifolds by Global Alignment of Local Linear Models
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
Jakob J. Verbeek
ICML
1998
IEEE
14 years 6 months ago
Learning a Language-Independent Representation for Terms from a Partially Aligned Corpus
Cross-language latent semantic indexing is a method that learns useful languageindependent vector representations of terms through a statistical analysis of a documentaligned text...
Michael L. Littman, Fan Jiang, Greg A. Keim
BMCBI
2008
113views more  BMCBI 2008»
13 years 5 months ago
Investigating selection on viruses: a statistical alignment approach
Background: Two problems complicate the study of selection in viral genomes: Firstly, the presence of genes in overlapping reading frames implies that selection in one reading fra...
Saskia de Groot, Thomas Mailund, Gerton Lunter, Jo...
EMNLP
2007
13 years 6 months ago
Syntactic Re-Alignment Models for Machine Translation
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Jonathan May, Kevin Knight