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RTB Formulation Using Point Process

arXiv 2308.09122 ↗First posted 17 Aug 2023stat.ML cs.GT cs.LGcited by 0

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Abstract (arXiv)

We propose a general stochastic framework for modelling repeated auctions in the Real Time Bidding (RTB) ecosystem using point processes. The flexibility of the framework allows a variety of auction scenarios including configuration of information provided to player, determination of auction winner and quantification of utility gained from each auctions. We propose theoretical results on how this formulation of process can be approximated to a Poisson point process, which enables the analyzer to take advantage of well-established properties. Under this framework, we specify the player's optimal strategy under various scenarios. We also emphasize that it is critical to consider the joint distribution of utility and market condition instead of estimating the marginal distributions independently.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 27 references that are in the map. First posted on arXiv 17 Aug 2023.

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References · 10

  1. 2021Robust Auction Design in the Auto-bidding Worldcited by 21
  2. 2020Online Joint Bid/Daily Budget Optimization of Internet Advertising Campaignscited by 16
  3. 2020Learning in repeated auctionscited by 15
  4. 2021An Efficient Deep Distribution Network for Bid Shading in First-Price Auctionscited by 14
  5. 2019Deep Landscape Forecasting for Real-time Bidding Advertisingcited by 12
  6. 2015Optimal Real-Time Bidding Strategiescited by 8
  7. 2019Learning to bid in revenue-maximizing auctionscited by 7
  8. 2022Bidding Agent Design in the LinkedIn Ad Marketplacecited by 7
  9. 2020Scalable Bid Landscape Forecasting in Real-time Biddingcited by 6
  10. 2020Optimal Bidding Strategies for Online Ad Auctions with Overlapping Targeting Criteriacited by 1

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