45 search results - page 1 / 9 » Model Adaptation via Model Interpolation and Boosting for We... |
EMNLP
2009
13 years 2 months ago
2009
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
IR
2010
13 years 3 months ago
2010
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
CIKM
2008
Springer
13 years 6 months ago
2008
Springer
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
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...
COLING
2010
12 years 11 months ago
2010
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...