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» Regression Relevance Models for Data Fusion
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BMCBI
2010
182views more  BMCBI 2010»
13 years 7 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
WWW
2008
ACM
14 years 8 months ago
Contextual advertising by combining relevance with click feedback
Contextual advertising supports much of the Web's ecosystem today. User experience and revenue (shared by the site publisher ad the ad network) depend on the relevance of the...
Deepayan Chakrabarti, Deepak Agarwal, Vanja Josifo...
BMCBI
2011
12 years 11 months ago
Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis
Background: Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these patholog...
Lionel Blanchet, Agnieszka Smolinska, Amos Attali,...
DIS
2006
Springer
13 years 11 months ago
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Marc Boullé, Carine Hue
CIKM
2009
Springer
14 years 1 months ago
Translating relevance scores to probabilities for contextual advertising
Information retrieval systems conventionally assess document relevance using the bag of words model. Consequently, relevance scores of documents retrieved for different queries a...
Deepak Agarwal, Evgeniy Gabrilovich, Robert Hall, ...