4 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
Randomized Truthful Auctions with Learning Agents
Gagan Aggarwal, Anupam Gupta, Andres Perlroth +1
We study a setting where agents use no-regret learning algorithms to participate in repeated auctions. \citet{kolumbus2022auctions} showed, rather surprisingly, that when bidders p…
Auto-bidding and Auctions in Online Advertising: A Survey
Gagan Aggarwal, Ashwinkumar Badanidiyuru, Santiago R. Balseiro +23
In this survey, we summarize recent developments in research fueled by the growing adoption of automated bidding strategies in online advertising. We explore the challenges and opp…
Platform Competition in the Autobidding World
Gagan Aggarwal, Andres Perlroth, Ariel Schvartzman +1
We study the problem of auction design for advertising platforms that face strategic advertisers who are bidding across platforms. Each advertiser's goal is to maximize their total…
Multi-Channel Auction Design in the Autobidding World
Gagan Aggarwal, Andres Perlroth, Junyao Zhao
Over the past few years, more and more Internet advertisers have started using automated bidding for optimizing their advertising campaigns. Such advertisers have an optimization g…
Efficiency of non-truthful auctions under auto-bidding
Christopher Liaw, Aranyak Mehta, Andres Perlroth
Auto-bidding is now widely adopted as an interface between advertisers and internet advertising as it allows advertisers to specify high-level goals, such as maximizing value subje…
Maximizing revenue in the presence of intermediaries
Gagan Aggarwal, Kshipra Bhawalkar, Guru Guruganesh +1
We study the mechanism design problem of selling items to unit-demand buyers with private valuations for the items. A buyer either participates directly in the auction or is re…