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IDA
2005
Springer
15 years 12 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer
CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 5 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
182
Voted
ECAI
2010
Springer
15 years 4 months ago
Describing the Result of a Classifier to the End-User: Geometric-based Sensitivity
This paper addresses the issue of supporting the end-user of a classifier, when it is used as a decision support system, to classify new cases. We consider several kinds of classif...
Isabelle Alvarez, Sophie Martin, Salma Mesmoudi
ICML
2010
IEEE
15 years 7 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
210
Voted
MCS
2009
Springer
16 years 1 months ago
True Path Rule Hierarchical Ensembles
Abstract. Hierarchical classification problems gained increasing attention within the machine learning community, and several methods for hierarchically structured taxonomies have...
Giorgio Valentini