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» Gene function prediction using labeled and unlabeled data
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EMNLP
2007
14 years 11 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
EMNLP
2011
13 years 9 months ago
Universal Morphological Analysis using Structured Nearest Neighbor Prediction
In this paper, we consider the problem of unsupervised morphological analysis from a new angle. Past work has endeavored to design unsupervised learning methods which explicitly o...
Young-Bum Kim, João Graça, Benjamin ...
BMCBI
2010
160views more  BMCBI 2010»
14 years 10 months ago
Extracting consistent knowledge from highly inconsistent cancer gene data sources
Background: Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diver...
Xue Gong, Ruihong Wu, Yuannv Zhang, Wenyuan Zhao, ...
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SDM
2009
SIAM
105views Data Mining» more  SDM 2009»
15 years 7 months ago
Exploiting Semantic Constraints for Estimating Supersenses with CRFs.
The annotation of words and phrases by ontology concepts is extremely helpful for semantic interpretation. However many ontologies, e.g. WordNet, are too fine-grained and even hu...
Gerhard Paaß, Frank Reichartz
BMCBI
2006
98views more  BMCBI 2006»
14 years 10 months ago
In search of functional association from time-series microarray data based on the change trend and level of gene expression
Background: The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional l...
Feng He, An-Ping Zeng