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» Label Ranking Methods based on the Plackett-Luce Model
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SIGIR
2012
ACM
11 years 8 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
ECML
2006
Springer
13 years 9 months ago
Case-Based Label Ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. We approach this setting from a case-based perspective and propo...
Klaus Brinker, Eyke Hüllermeier
ECML
2007
Springer
13 years 7 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari
JMLR
2012
11 years 8 months ago
Perturbation based Large Margin Approach for Ranking
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Eunho Yang, Ambuj Tewari, Pradeep D. Ravikumar
CVPR
2011
IEEE
13 years 2 months ago
Image Ranking and Retrieval Based on Multi-Attribute Queries
We propose a novel approach for ranking and retrieval of images based on multi-attribute queries. Existing image retrieval methods train separate classifiers for each word and he...
Behjat Siddiquie, Rogerio Feris, Larry Davis