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» Semi-supervised Learning from General Unlabeled Data
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KDD
2008
ACM
206views Data Mining» more  KDD 2008»
14 years 8 months ago
Identifying biologically relevant genes via multiple heterogeneous data sources
Selection of genes that are differentially expressed and critical to a particular biological process has been a major challenge in post-array analysis. Recent development in bioin...
Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, Y...
TLCA
2005
Springer
14 years 1 months ago
Privacy in Data Mining Using Formal Methods
There is growing public concern about personal data collected by both private and public sectors. People have very little control over what kinds of data are stored and how such da...
Stan Matwin, Amy P. Felty, István T. Hern&a...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
BMCBI
2006
142views more  BMCBI 2006»
13 years 8 months ago
Improving the Performance of SVM-RFE to Select Genes in Microarray Data
Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
Yuanyuan Ding, Dawn Wilkins
WSDM
2010
ACM
261views Data Mining» more  WSDM 2010»
14 years 5 months ago
Learning Similarity Metrics for Event Identification in Social Media
Social media sites (e.g., Flickr, YouTube, and Facebook) are a popular distribution outlet for users looking to share their experiences and interests on the Web. These sites host ...
Hila Becker, Mor Naaman, Luis Gravano