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» Information Theory, Inference, and Learning Algorithms
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ROCAI
2004
Springer
14 years 1 months 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
SIGIR
2003
ACM
14 years 1 months ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
TOPLAS
2008
81views more  TOPLAS 2008»
13 years 8 months ago
Size-change termination with difference constraints
lem of inferring termination from such abstract information is not the halting problem for programs and may well be decidable. If this is the case, the decision algorithm forms a &...
Amir M. Ben-Amram
CVPR
2007
IEEE
14 years 10 months ago
Detector Ensemble
Component-based detection methods have demonstrated their promise by integrating a set of part-detectors to deal with large appearance variations of the target. However, an essent...
Shengyang Dai, Ming Yang, Ying Wu, Aggelos K. Kats...
EMNLP
2009
13 years 5 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti