Preference learning

Preference learning is a subfield in machine learning in which the goal is to learn a predictive preference model from observed preference… (More)
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Papers overview

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2016
2016
A social recommendation system has attracted a lot of attention recently in the research communities of information retrieval… (More)
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2015
2015
Preference learning (PL) is a core area of machine learning that handles datasets with ordinal relations. As the number of… (More)
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Highly Cited
2011
Highly Cited
2011
Information theoretic active learning has been widely studied for probabilistic models. For simple regression an optimal myopic… (More)
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2009
2009
There is an increasing trend towards personalization of services and interaction. The use of computational models for learning to… (More)
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Highly Cited
2008
Highly Cited
2008
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order… (More)
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Highly Cited
2005
Highly Cited
2005
Combining practical relevance with novel types of prediction problems, the learning from/of preferences has recently received a… (More)
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Highly Cited
2005
Highly Cited
2005
In this paper, we propose a probabilistic kernel approach to preference learning based on Gaussian processes. A new likelihood… (More)
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Highly Cited
2004
Highly Cited
2004
In decision making, in order to avoid misleading solutions, the study of consistency when the decision makers express their… (More)
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Highly Cited
2003
Highly Cited
2003
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels… (More)
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Highly Cited
2002
Highly Cited
2002
Personalization of e-services poses new challenges to database technology. In particular, a powerful and flexible modeling… (More)
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