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» Predicting Success in Machine Translation
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EMNLP
2008
13 years 9 months ago
A Simple and Effective Hierarchical Phrase Reordering Model
While phrase-based statistical machine translation systems currently deliver state-of-theart performance, they remain weak on word order changes. Current phrase reordering models ...
Michel Galley, Christopher D. Manning
COLING
1996
13 years 8 months ago
Learning to Recognize Names Across Languages
The development of natural language proccssing (NLP) systems that perform machine translation (MT) and information retrieval (IR) has highlighted the need for the automatic recogn...
Anthony F. Gallippi
ICML
2009
IEEE
14 years 2 months ago
Active learning for directed exploration of complex systems
Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fid...
Michael C. Burl, Esther Wang
COLT
2008
Springer
13 years 9 months ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
BMCBI
2006
85views more  BMCBI 2006»
13 years 7 months ago
Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy
Background: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have bee...
Rui Jiang, Hua Yang, Fengzhu Sun, Ting Chen