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» Learning Preferences for Multiclass Problems
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EMNLP
2010
13 years 5 months ago
Confidence in Structured-Prediction Using Confidence-Weighted Models
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
Avihai Mejer, Koby Crammer
ECML
2003
Springer
14 years 29 days ago
Pairwise Preference Learning and Ranking
We consider supervised learning of a ranking function, which is a mapping from instances to total orders over a set of labels (options). The training information consists of exampl...
Johannes Fürnkranz, Eyke Hüllermeier
ECCV
2010
Springer
14 years 1 months ago
Robust Multi-View Boosting with Priors
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....

Publication
154views
12 years 10 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
IJCNN
2007
IEEE
14 years 2 months ago
Preference Learning for Category-Ranking based Interactive Text Categorization
— Category Ranking is a variant of the multi-label classification problem, in which, rather than performing a (hard) assignment to an object of categories from a predefined set...
Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sper...