# RTB Formulation Using Point Process

arXiv: https://arxiv.org/abs/2308.09122 · HTML: https://mlsanity.com/paper/2308.09122/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 27 references that are in the map.
- First posted on arXiv 17 Aug 2023.

## Builds on (most cited first, 10 of 10)

- [Robust Auction Design in the Auto-bidding World](https://mlsanity.com/paper/2111.02468/) (2021)
- [Online Joint Bid/Daily Budget Optimization of Internet Advertising Campaigns](https://mlsanity.com/paper/2003.01452/) (2020)
- [Learning in repeated auctions](https://mlsanity.com/paper/2011.09365/) (2020)
- [An Efficient Deep Distribution Network for Bid Shading in First-Price Auctions](https://mlsanity.com/paper/2107.06650/) (2021)
- [Deep Landscape Forecasting for Real-time Bidding Advertising](https://mlsanity.com/paper/1905.03028/) (2019)
- [Optimal Real-Time Bidding Strategies](https://mlsanity.com/paper/1511.08409/) (2015)
- [Learning to bid in revenue-maximizing auctions](https://mlsanity.com/paper/1902.10427/) (2019)
- [Bidding Agent Design in the LinkedIn Ad Marketplace](https://mlsanity.com/paper/2202.12472/) (2022)
- [Scalable Bid Landscape Forecasting in Real-time Bidding](https://mlsanity.com/paper/2001.06587/) (2020)
- [Optimal Bidding Strategies for Online Ad Auctions with Overlapping Targeting Criteria](https://mlsanity.com/paper/2004.07190/) (2020)

## 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.