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» An Instance Selection Approach to Multiple Instance Learning
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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
14 years 7 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
PICS
2003
14 years 11 months ago
Selection of Training Sets for the Characterisation of Multispectral Imaging Systems
To establish a correlation between the system output and the corresponding reflectance, the system characterisation functionDeriving the actual multispectral data from the output o...
Paolo Pellegri, Gianluca Novati, Raimondo Schettin...
AAAI
1996
14 years 11 months ago
Bagging, Boosting, and C4.5
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classi er learning systems. Both form a set of classi ers t...
J. Ross Quinlan
ICML
2010
IEEE
14 years 11 months ago
Label Ranking Methods based on the Plackett-Luce Model
This paper introduces two new methods for label ranking based on a probabilistic model of ranking data, called the Plackett-Luce model. The idea of the first method is to use the ...
Weiwei Cheng, Krzysztof Dembczynski, Eyke Hül...
CVPR
2007
IEEE
15 years 12 months ago
Accurate Object Detection with Deformable Shape Models Learnt from Images
We present an object class detection approach which fully integrates the complementary strengths offered by shape matchers. Like an object detector, it can learn class models dire...
Cordelia Schmid, Frédéric Jurie, Vit...