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» Label Ranking Methods based on the Plackett-Luce Model
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ICASSP
2010
IEEE
15 years 15 hour ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
DASFAA
2009
IEEE
133views Database» more  DASFAA 2009»
15 years 6 months ago
Probabilistic Ranking in Uncertain Vector Spaces
Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
ECAI
2004
Springer
15 years 3 months ago
Instance-Based Prediction with Guaranteed Confidence
Instance-based learning (IBL) algorithms have proved to be successful in many applications. However, as opposed to standard statistical methods, a prediction in IBL is usually give...
Eyke Hüllermeier
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 11 days ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...
ICDAR
2003
IEEE
15 years 5 months ago
A Segmentation Method for Bibliographic References by Contextual Tagging of Fields
In this paper, a method based on part-of-speech tagging (PoS) is used for bibliographic reference structure. This method operates on a roughly structured ASCII file, produced by O...
Dominique Besagni, Abdel Belaïd, Nelly Benet