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» Managing Domain Knowledge and Multiple Models with Boosting
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IJCAI
2007
13 years 6 months ago
Managing Domain Knowledge and Multiple Models with Boosting
We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
Peng Zang, Charles Lee Isbell Jr.
CVPR
2010
IEEE
13 years 5 months ago
Boosting for transfer learning with multiple sources
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
Yi Yao, Gianfranco Doretto
AAAI
2012
11 years 7 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...
CLA
2006
13 years 6 months ago
First Elements on Knowledge Discovery Guided by Domain Knowledge (KDDK)
In this paper, we present research trends carried out in the Orpailleur team at loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge disco...
Jean Lieber, Amedeo Napoli, Laszlo Szathmary, Yann...
PAMI
2012
11 years 7 months ago
UBoost: Boosting with the Universum
—It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training...
Chunhua Shen, Peng Wang, Fumin Shen, Hanzi Wang