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ECIR
2011
Springer
12 years 11 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
RSFDGRC
2005
Springer
151views Data Mining» more  RSFDGRC 2005»
14 years 1 months ago
DIXER - Distributed Executor for Rough Set Exploration System
We present the Distributed Executor for RSES (DIXER) which is a supplementary software for the Rough Set Exploration System (RSES). It takes an advantage of grid computing paradigm...
Jan G. Bazan, Rafal Latkowski, Marcin S. Szczuka
ICML
2007
IEEE
14 years 8 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
DASFAA
2005
IEEE
141views Database» more  DASFAA 2005»
14 years 1 months ago
Learning Tree Augmented Naive Bayes for Ranking
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
NIPS
2007
13 years 9 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
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...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...