Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
Aleksandrs Slivkins and Filip Radlinski and Sreenivas Gollapudi

Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections.pdf 325.55kB
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@article{14:14,author={Aleksandrs Slivkins and Filip Radlinski and Sreenivas Gollapudi}, Title={Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections},journal={Journal of Machine Learning Research},volume={14}, url={http://www.jmlr.org/papers/volume14/slivkins13a/slivkins13a.pdf}}
Citation:
Slivkins, A., Radlinski, F., & Gollapudi, S.. (2014). Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections [Data set]. Academic Torrents. https://academictorrents.com/details/07eaf4e61b499e738b1283822e747bdb6c822993
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