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WWW
2008
ACM
14 years 8 months ago
Ranking refinement and its application to information retrieval
We consider the problem of ranking refinement, i.e., to improve the accuracy of an existing ranking function with a small set of labeled instances. We are, particularly, intereste...
Rong Jin, Hamed Valizadegan, Hang Li
COLT
2005
Springer
14 years 1 months ago
Margin-Based Ranking Meets Boosting in the Middle
Abstract. We present several results related to ranking. We give a general margin-based bound for ranking based on the L∞ covering number of the hypothesis space. Our bound sugge...
Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robe...
CIKM
2009
Springer
14 years 2 months ago
Learning to rank from Bayesian decision inference
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 ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
EMNLP
2009
13 years 5 months ago
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
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...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
14 years 2 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...