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» Learning Models for Predicting Recognition Performance
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EMNLP
2011
13 years 11 months ago
Structured Sparsity in Structured Prediction
Linear models have enjoyed great success in structured prediction in NLP. While a lot of progress has been made on efficient training with several loss functions, the problem of ...
André F. T. Martins, Noah A. Smith, M&aacut...
BMCBI
2006
127views more  BMCBI 2006»
14 years 11 months ago
A graph-search framework for associating gene identifiers with documents
Background: One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation ...
William W. Cohen, Einat Minkov
BMCBI
2010
98views more  BMCBI 2010»
14 years 12 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
BMCBI
2007
113views more  BMCBI 2007»
14 years 11 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
SP
2002
IEEE
134views Security Privacy» more  SP 2002»
14 years 11 months ago
Performance engineering, PSEs and the GRID
Performance Engineering is concerned with the reliable prediction and estimation of the performance of scientific and engineering applications on a variety of parallel and distrib...
Tony Hey, Juri Papay