Adaptive Bid Shading Optimization of First-Price Ad Inventory

January 24, 2021

Abstract

This paper proposes an adaptive scheme for online learning of optimal bid shading. The scheme involves segmentation, a two-parametric nonlinear shading mechanism, and an online learning algorithm for parameter optimization. The learning algorithm employs recursive least squares estimation of a log-quadratic approximation of the relationship between the surplus and the parameters, and a Newton-like gradient descent update scheme to find the surplus maximizing shading parameters.

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Publication Type

Paper

Conference / Journal Name

ACC 2021

Authors

Niklas Karlsson

Qian Sang

BibTeX


@inproceedings{
    author = {},
    title = {‌Adaptive Bid Shading Optimization of First-Price Ad Inventory‌},
    booktitle = {Proceedings of ACC 2021‌},
    year = {‌2021‌}
}