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» The Feature Subspace Method for SMT System Combination
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EMNLP
2009
13 years 5 months ago
The Feature Subspace Method for SMT System Combination
Recently system combination has been shown to be an effective way to improve translation quality over single machine translation systems. In this paper, we present a simple and ef...
Nan Duan, Mu Li, Tong Xiao, Ming Zhou
FGR
2004
IEEE
200views Biometrics» more  FGR 2004»
13 years 11 months ago
Using Random Subspace to Combine Multiple Features for Face Recognition
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
Xiaogang Wang, Xiaoou Tang
BMCBI
2011
13 years 2 months ago
Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
Background: Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture th...
Bailing Zhang, Tuan D. Pham
EMNLP
2010
13 years 5 months ago
Combining Unsupervised and Supervised Alignments for MT: An Empirical Study
Word alignment plays a central role in statistical MT (SMT) since almost all SMT systems extract translation rules from word aligned parallel training data. While most SMT systems...
Jinxi Xu, Antti-Veikko I. Rosti
COLING
2010
13 years 2 months ago
Feature-Rich Discriminative Phrase Rescoring for SMT
This paper proposes a new approach to phrase rescoring for statistical machine translation (SMT). A set of novel features capturing the translingual equivalence between a source a...
Fei Huang, Bing Xiang