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» Top-k learning to rank: labeling, ranking and evaluation
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ECTEL
2007
Springer
15 years 3 months ago
Relevance Ranking Metrics for Learning Objects
— The main objetive of this paper is to improve the current status of learning object search. First, the current situation is analyzed and a theretical solution, based on relevan...
Xavier Ochoa, Erik Duval
62
Voted
PPSN
2004
Springer
15 years 3 months ago
Ensemble Learning with Evolutionary Computation: Application to Feature Ranking
Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings ext...
Kees Jong, Elena Marchiori, Michèle Sebag
CIARP
2009
Springer
15 years 4 months ago
Dealing with Inaccurate Face Detection for Automatic Gender Recognition with Partially Occluded Faces
Abstract. Gender recognition problem has not been extensively studied in situations where the face cannot be accurately detected and it also can be partially occluded. In this cont...
Yasmina Andreu, Pedro García-Sevilla, Ram&o...
85
Voted
ICML
2010
IEEE
14 years 7 months ago
Learning optimally diverse rankings over large document collections
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
ECIR
2011
Springer
14 years 1 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke