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KDD
2001
ACM
163views Data Mining» more  KDD 2001»
14 years 9 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...
WSDM
2010
ACM
365views Data Mining» more  WSDM 2010»
14 years 6 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»
14 years 4 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»
14 years 3 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
KDD
2007
ACM
124views Data Mining» more  KDD 2007»
14 years 3 months ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
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