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ISMB
1993
15 years 8 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
CORR
2010
Springer
210views Education» more  CORR 2010»
15 years 6 months ago
Test Case Generation for Object-Oriented Imperative Languages in CLP
Testing is a vital part of the software development process. Test Case Generation (TCG) is the process of automatically generating a collection of test-cases which are applied to ...
Miguel Gómez-Zamalloa, Elvira Albert, Germ&...
TMI
2008
154views more  TMI 2008»
15 years 6 months ago
Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models
In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discrimin...
Zhuowen Tu, Katherine Narr, Piotr Dollár, I...
EMNLP
2009
15 years 4 months ago
Natural Language Generation with Tree Conditional Random Fields
This paper presents an effective method for generating natural language sentences from their underlying meaning representations. The method is built on top of a hybrid tree repres...
Wei Lu, Hwee Tou Ng, Wee Sun Lee
EMNLP
2009
15 years 4 months ago
Bilingual dictionary generation for low-resourced language pairs
Bilingual dictionaries are vital resources in many areas of natural language processing. Numerous methods of machine translation require bilingual dictionaries with large coverage...
István Varga, Shoichi Yokoyama