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» Prediction of Learning Curves in Machine Translation
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ICML
2008
IEEE
14 years 7 months ago
Training structural SVMs when exact inference is intractable
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...
Thomas Finley, Thorsten Joachims
ICMLA
2010
13 years 4 months ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 10 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
COLT
2008
Springer
13 years 8 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
IJFCS
2006
130views more  IJFCS 2006»
13 years 6 months ago
Mealy multiset automata
We introduce the networks of Mealy multiset automata, and study their computational power. The networks of Mealy multiset automata are computationally complete. 1 Learning from Mo...
Gabriel Ciobanu, Viorel Mihai Gontineac