68 search results - page 2 / 14 » A General Boosting Method and its Application to Learning Ra... |
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, ...
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. ...
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...
CIKM
2009
Springer
13 years 11 months ago
2009
Springer
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
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...