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» Maximal Vector Computation in Large Data Sets
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JMLR
2008
230views more  JMLR 2008»
14 years 9 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
BMCBI
2005
142views more  BMCBI 2005»
14 years 9 months ago
transAlign: using amino acids to facilitate the multiple alignment of protein-coding DNA sequences
Background: Alignments of homologous DNA sequences are crucial for comparative genomics and phylogenetic analysis. However, multiple alignment represents a computationally difficu...
Olaf R. P. Bininda-Emonds
CONSTRAINTS
2010
153views more  CONSTRAINTS 2010»
14 years 7 months ago
Philosophy of the MiniZinc challenge
MiniZinc arose as a response to the extended discussion at CP2006 of the need for a standard modelling language for CP. This is a challenging problem, and we believe MiniZinc makes...
Peter J. Stuckey, Ralph Becket, Julien Fischer
BMCBI
2007
144views more  BMCBI 2007»
14 years 9 months ago
Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study an
Background: Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. ...
Dennis R. Livesay, Patrick D. Kidd, Sepehr Eskanda...
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CIKM
2011
Springer
13 years 9 months ago
Lower-bounding term frequency normalization
In this paper, we reveal a common deficiency of the current retrieval models: the component of term frequency (TF) normalization by document length is not lower-bounded properly;...
Yuanhua Lv, ChengXiang Zhai