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» Machine Translation System Combination by Confusion Forest
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EMNLP
2008
14 years 11 months ago
Lattice-based Minimum Error Rate Training for Statistical Machine Translation
Minimum Error Rate Training (MERT) is an effective means to estimate the feature function weights of a linear model such that an automated evaluation criterion for measuring syste...
Wolfgang Macherey, Franz Josef Och, Ignacio Thayer...
CHI
2009
ACM
15 years 10 months ago
EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers
Machine learning is an increasingly used computational tool within human-computer interaction research. While most researchers currently utilize an iterative approach to refining ...
Justin Talbot, Bongshin Lee, Ashish Kapoor, Desney...
ACL
2010
14 years 7 months ago
Error Detection for Statistical Machine Translation Using Linguistic Features
Automatic error detection is desired in the post-processing to improve machine translation quality. The previous work is largely based on confidence estimation using system-based ...
Deyi Xiong, Min Zhang, Haizhou Li
NAACL
2010
14 years 7 months ago
Improved Models of Distortion Cost for Statistical Machine Translation
The distortion cost function used in Mosesstyle machine translation systems has two flaws. First, it does not estimate the future cost of known required moves, thus increasing sea...
Spence Green, Michel Galley, Christopher D. Mannin...
ACCV
2010
Springer
14 years 4 months ago
Randomised Manifold Forests for Principal Angle-Based Face Recognition
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
Ujwal D. Bonde, Tae-Kyun Kim, K. R. Ramakrishnan