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» Metric Learning to Rank
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117
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SIGIR
2009
ACM
15 years 9 months ago
A bayesian learning approach to promoting diversity in ranking for biomedical information retrieval
In this paper, we propose a Bayesian learning approach to promoting diversity for information retrieval in biomedicine and a re-ranking model to improve retrieval performance in t...
Xiangji Huang, Qinmin Hu
ICML
2008
IEEE
16 years 4 months ago
Multiple instance ranking
This paper introduces a novel machine learning model called multiple instance ranking (MIRank) that enables ranking to be performed in a multiple instance learning setting. The mo...
Charles Bergeron, Jed Zaretzki, Curt M. Breneman, ...
157
Voted
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
13 years 11 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
CVPR
2012
IEEE
13 years 5 months ago
Non-negative low rank and sparse graph for semi-supervised learning
Constructing a good graph to represent data structures is critical for many important machine learning tasks such as clustering and classification. This paper proposes a novel no...
Liansheng Zhuang, Haoyuan Gao, Zhouchen Lin, Yi Ma...
IR
2010
15 years 1 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...