No-Regret Algorithms in non-Truthful Auctions with Budget and ROI Constraints
Advertisers are increasingly using automated bidding to optimize their ad campaigns on online advertising platforms. Autobidding allows an advertiser to optimize her objective subject to various constraints. In this paper, we design online autobidding algorithms to optimize value subject to ROI and budget constraints.
Authors
- Mingfei Zhao (ORCID: https://orcid.org/0000-0002-8008-0922)
- Giannis Fikioris (ORCID: https://orcid.org/0000-0002-4920-478X)
- Gagan Aggarwal (ORCID: https://orcid.org/0009-0003-3296-4891)
Institutions
- Google (United States) (US)
- Cornell University (US)
Publication Details
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1145/3696410.3714881
- Citations
- 1
- Primary Topic
- Auction Theory and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.11
Funders
- U.S. Department of Defense
- Alexander S. Onassis Public Benefit Foundation
- National Defense Science and Engineering Graduate
- Air Force Office of Scientific Research