Abstract
We study how web publishers should set their floor prices in order to maximize expected revenues when they have access to two selling mechanisms, namely an ad exchange and header bidding, in order to sell impressions on the real-time bidding market. We consider the publisher’s problem under incomplete information, propose bandit-type algorithms, and show that their regret – the performance loss compared to the optimal algorithm – is sub-linear in the time horizon. Experiments illustrate the effectiveness of our algorithms.
Original language | English |
---|---|
Pages (from-to) | 250-256 |
Number of pages | 7 |
Journal | Operations Research Letters |
Volume | 49 |
Issue number | 2 |
DOIs | |
Publication status | Published - Mar 2021 |
Keywords
- Auctions
- Floor price
- Header bidding
- Machine learning
- Multi-armed bandits
- Pricing