Michelle Brachman, Qian Pan, et al.
IUI 2023
We propose and evaluate a number of improvements to the linear programming formulation of web advertisement scheduling, which we have proposed elsewhere together with our colleagues [Langheinrich et al., 9]. In particular, we address a couple of important technical challenges having to do with the estimation of click-through rates and optimization of display probabilities (the exploration-exploitation trade-off and the issue of data sparseness and sealability). as well as practical aspects that are essential for successful deployment of this approach (the issues of multi-impressions and inventory management). We propose solutions to each of these issues, and assess their effectiveness by running large-scale simulation experiments. © 2005 Springer Science + Business Media. Inc.
Michelle Brachman, Qian Pan, et al.
IUI 2023
D. Oliveira, R. Silva Ferreira, et al.
EAGE/PESGB Workshop Machine Learning 2018
Elron Bandel, Ranit Aharonov, et al.
ACL 2022
Amy Hurst, Scott E. Hudson, et al.
IUI 2008