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
Type: Paper
Tags:

Metadata: 
@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
No stats to report yet.
Related Torrents
Report
Send Feedback Start
   0.000004
DB Connect
   0.000472
Lookup hash in DB
   0.000466
Get torrent details
   0.000116
Get torrent details, finished
   0.000207
Get authors
   0.000000
Select authors
   0.000206
Parse bibtex
   0.000089
Write header
   0.000352
get stars
   0.000111
home tab
   0.000101
render right panel
   0.000004
render ads
   0.000375
fetch current hosters
   0.000215
Start get stats
   0.001252
End get stats
   0.000002
related datasets
   0.000806
Done