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» Gene function prediction using labeled and unlabeled data
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ACL
2006
14 years 11 months ago
Relation Extraction Using Label Propagation Based Semi-Supervised Learning
Shortage of manually labeled data is an obstacle to supervised relation extraction methods. In this paper we investigate a graph based semi-supervised learning algorithm, a label ...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
PRIB
2009
Springer
187views Bioinformatics» more  PRIB 2009»
15 years 2 months ago
Semi-supervised Prediction of Protein Interaction Sentences Exploiting Semantically Encoded Metrics
Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification ...
Tamara Polajnar, Mark A. Girolami
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
15 years 10 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
79
Voted
CVPR
2008
IEEE
16 years 3 days ago
Active microscopic cellular image annotation by superposable graph transduction with imbalanced labels
Systematic content screening of cell phenotypes in microscopic images has been shown promising in gene function understanding and drug design. However, manual annotation of cells ...
Jun Wang, Shih-Fu Chang, Xiaobo Zhou, Stephen T. C...
97
Voted
COLING
2010
14 years 5 months ago
Active Deep Networks for Semi-Supervised Sentiment Classification
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
Shusen Zhou, Qingcai Chen, Xiaolong Wang