550 search results - page 1 / 110 » A general magnitude-preserving boosting algorithm for search... |
CIKM
2009
Springer
13 years 11 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....
NIPS
2007
13 years 6 months ago
2007
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
WWW
2011
ACM
12 years 11 months ago
2011
ACM
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
KDD
2010
ACM
13 years 8 months ago
2010
ACM
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...