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KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 7 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen
KDD
2004
ACM
112views Data Mining» more  KDD 2004»
16 years 7 months ago
A rank sum test method for informative gene discovery
Finding informative genes from microarray data is an important research problem in bioinformatics research and applications. Most of the existing methods rank features according t...
Lin Deng, Jian Pei, Jinwen Ma, Dik Lun Lee
WSDM
2010
ACM
365views Data Mining» more  WSDM 2010»
16 years 4 months ago
A Novel Click Model and Its Applications to Online Advertising
Recent advances in click model have positioned it as an attractive method for representing user preferences in web search and online advertising. Yet, most of the existing works f...
Zeyuan Allen Zhu, Weizhu Chen, Tom Minka, Chenguan...
WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
16 years 1 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
ICDM
2008
IEEE
150views Data Mining» more  ICDM 2008»
16 years 1 months ago
Pseudolikelihood EM for Within-network Relational Learning
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Rongjing Xiang, Jennifer Neville
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