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» Learning to rank at query-time using association rules
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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
ROCAI
2004
Springer
14 years 28 days ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
JMLR
2010
117views more  JMLR 2010»
13 years 2 months ago
Exploiting the High Predictive Power of Multi-class Subgroups
Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. A number of multi-class subgroup disc...
Tarek Abudawood, Peter A. Flach
BMCBI
2010
154views more  BMCBI 2010»
13 years 7 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
IJON
2006
109views more  IJON 2006»
13 years 7 months ago
Associative memory of connectivity patterns
The goal of the visual correspondence problem is to establish a connectivity pattern (a mapping) between two images such that features projected from the same scene point are conn...
Junmei Zhu, Christoph von der Malsburg