281 search results - page 7 / 57 » Group-based learning: a boosting approach |
CIKM
2000
Springer
13 years 11 months ago
2000
Springer
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
IJCAI
2003
13 years 8 months ago
2003
Ensemble methods like bagging and boosting that combine the decisions of multiple hypotheses are some of the strongest existing machine learning methods. The diversity of the memb...
CIKM
2009
Springer
14 years 2 months ago
2009
Springer
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...