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» Learning Models for Predicting Recognition Performance
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EMNLP
2011
13 years 9 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 9 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 9 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 9 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 9 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