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Yuan Deng

16 papers hereh-index 13833 citations46 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author13
  • middle author2
  • last author1

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.GT15
  • econ.TH1
same name
  • Yuan Deng — 7 papers, h 3
  • Yuan Deng — 5 papers, h 4
  • Yuan Deng — 1 paper, h 2
  • Yuan Deng — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152026
most citedMulti-channel Autobidding with Budget and ROI Constraints

9 citations · 20 across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.GT2023★ 1 cited

Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study

Yuan Deng, Jieming Mao, Vahab Mirrokni +2

In recent years, the growing adoption of autobidding has motivated the study of auction design with value-maximizing auto-bidders. It is known that under mild assumptions, uniform…

cs.GT2023★ 1 cited

Efficiency of the Generalized Second-Price Auction for Value Maximizers

Yuan Deng, Mohammad Mahdian, Jieming Mao +3

We study the price of anarchy of the generalized second-price auction where bidders are value maximizers (i.e., autobidders). We show that in general the price of anarchy can be as…

cs.GT2023★ 9 cited

Multi-channel Autobidding with Budget and ROI Constraints

Yuan Deng, Negin Golrezaei, Patrick Jaillet +2

In digital online advertising, advertisers procure ad impressions simultaneously on multiple platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of w…

cs.GT2023

Autobidding Auctions in the Presence of User Costs

Yuan Deng, Jieming Mao, Vahab Mirrokni +2

We study autobidding ad auctions with user costs, where each bidder is value-maximizing subject to a return-over-investment (ROI) constraint, and the seller aims to maximize the so…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.