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Aranyak Mehta

17 papers hereh-index 275.4k citations103 works total

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

author position
  • sole author1
  • first author2
  • middle author10
  • last author3

Across the 16 of 17 papers where every author was matched, so the position is known.

fields
  • cs.GT11
  • cs.DS2
  • econ.TH2
  • cs.LG1
  • math.CO1
same name
  • Aranyak Mehta — 23 papers, h 6
  • Aranyak Mehta — 1 paper, h 1

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
20052023
most citedOnline Stochastic Matching: Beating 1-1/e

40 citations · 78 across the 17 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.GT2022★ 4 cited

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…

cs.GT2022

Prior-Independent Auctions for Heterogeneous Bidders

Guru Guruganesh, Aranyak Mehta, Di Wang +1

We study the design of prior-independent auctions in a setting with heterogeneous bidders. In particular, we consider the setting of selling to n bidders whose values are drawn f…

cs.GT2022★ 2 cited

Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions

Gagan Aggarwal, Kshipra Bhawalkar, Aranyak Mehta +2

Internet ad auctions have evolved from a few lines of text to richer informational layouts that include images, sitelinks, videos, etc. Ads in these new formats occupy varying amou…

cs.GT2022★ 1 cited

Auction Design in an Auto-bidding Setting: Randomization Improves Efficiency Beyond VCG

Aranyak Mehta

Auto-bidding is an area of increasing importance in the domain of online advertising. We study the problem of designing auctions in an auto-bidding setting with the goal of maximiz…

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