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Metric learning to rank (2010)
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by
Brian Mcfee
,
Gert Lanckriet
| Venue: | In Proceedings of the 27th annual International Conference on Machine Learning (ICML |
| Citations: | 59 - 9 self |
BibTeX
@INPROCEEDINGS{Mcfee10metriclearning,
author = {Brian Mcfee and Gert Lanckriet},
title = {Metric learning to rank},
booktitle = {In Proceedings of the 27th annual International Conference on Machine Learning (ICML},
year = {2010}
}
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Abstract
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that rankings of data induced by distance from a query can be optimized against various ranking measures, such as AUC, Precision-at-k, MRR, MAP or NDCG. We demonstrate experimental results on standard classification data sets, and a large-scale online dating recommendation problem. 1.
