@article{burgesRankNetLambdaRankLambdaMART2010,
  langid = {american},
  title = {From {{RankNet}} to {{LambdaRank}} to {{LambdaMART}}: {{An Overview}}},
  url = {https://www.microsoft.com/en-us/research/publication/from-ranknet-to-lambdarank-to-lambdamart-an-overview/},
  shorttitle = {From {{RankNet}} to {{LambdaRank}} to {{LambdaMART}}},
  abstract = {LambdaMART is the boosted tree version of LambdaRank, which is based on RankNet. RankNet, LambdaRank, and LambdaMART have proven to be very successful algorithms for solving real world ranking problems: for example an ensemble of LambdaMART rankers won Track 1 of the 2010 Yahoo! Learning To Rank Challenge. The details of these algorithms are spread …},
  urldate = {2019-02-15},
  date = {2010-06-23},
  author = {Burges, Chris J. C.},
  file = {/home/dimitri/Nextcloud/Zotero/storage/ZFV3AZ43/Burges - 2010 - From RankNet to LambdaRank to LambdaMART An Overv.pdf;/home/dimitri/Nextcloud/Zotero/storage/VCCSEGHK/from-ranknet-to-lambdarank-to-lambdamart-an-overview.html}
}

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