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» Maximum entropy methods for biological sequence modeling
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BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
15 years 3 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...
BMCBI
2010
178views more  BMCBI 2010»
14 years 12 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
RECOMB
2003
Springer
16 years 3 days ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
ACL
2006
15 years 1 months ago
Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing me...
Yuya Unno, Takashi Ninomiya, Yusuke Miyao, Jun-ich...
COLING
2000
15 years 1 months ago
A Hybrid Japanese Parser with Hand-crafted Grammar and Statistics
This paper describes a hybrid parsing method for Japanese which uses both a hand-crafted grammar and a statistical technique. The key feature of our system is that in order to est...
Hiroshi Kanayama, Kentaro Torisawa, Yutaka Mitsuis...