Yuan Deng
Yuan Deng is a Research Scientist at Google Research New York City. His research is broadly situated at the interface between economics and computer science (aka. algorithmic game theory), mainly including dynamic mechanism design (how to design auctions for online advertisement markets) and learning in economic environments (e.g. online pricing for strategic agents and/or learning agents).
Authored Publications
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Optimal Mechanisms for a Value Maximizer: The Futility of Screening Targets
Proceedings of the 25th ACM Conference on Economics and Computation (EC) (2024)
Auto-bidding and Auctions in Online Advertising: A Survey
Ashwinkumar Badanidiyuru Varadaraja
Christopher Liaw
Haihao (Sean) Lu
Andres Perlroth
Georgios Piliouras
Ariel Schvartzman
Kelly Spendlove
Hanrui Zhang
Mingfei Zhao
ACM SIGecom Exchanges, 22 (2024)
Efficiency of the Generalized Second-Price Auction for Value Maximizers
Hanrui Zhang
Proceedings of the ACM on Web Conference 2024, 46–56
Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice
Negin Golrezaei
Patrick Jaillet
Jason Cheuk Nam Liang
Proceedings of the ACM on Web Conference 2024, 267–275
Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study
Proceedings of the ACM on Web Conference 2024, 256–266
Multi-channel Autobidding with Budget and ROI Constraints
Negin Golrezaei
Patrick Jaillet
Jason Cheuk Nam Liang
Proceedings of the 40th International Conference on Machine Learning (2023), 7617–7644
Autobidding Auctions in the Presence of User Costs
Hanrui Zhang
Proceedings of the ACM Web Conference 2023, pp. 3428-3435
Optimal Pricing Schemes for an Impatient Buyer
Kangning Wang
Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (2023), pp. 382-398
