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Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems. (arXiv:2205.09809v1 [cs.LG])
May 23, 2022, 1:10 a.m. | Yewen Fan, Nian Si, Kun Zhang
cs.LG updates on arXiv.org arxiv.org
Calibration is defined as the ratio of the average predicted click rate to
the true click rate. The optimization of calibration is essential to many
online advertising recommendation systems because it directly affects the
downstream bids in ads auctions and the amount of money charged to advertisers.
Despite its importance, calibration optimization often suffers from a problem
called "maximization bias". Maximization bias refers to the phenomenon that the
maximum of predicted values overestimates the true maximum. The problem is
introduced …
advertising arxiv bias recommendation recommendation systems scale systems
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