MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising
Not on the map. Why?
Abstract (arXiv)
Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowadays, multi-slot display advertising is gradually becoming popular where many ads could be displayed in a list and shown as a whole to users. However, multi-slot display advertising leads to different cost-effectiveness. Advertisers have the incentive to adjust bid prices so as to win the most economical ad positions. In this study, we introduce bid shading into multi-slot display advertising for bid price adjustment with a Multi-task End-to-end Bid Shading(MEBS) method. We prove the optimality of our method theoretically and examine its performance experimentally. Through extensive offline and online experiments, we demonstrate the effectiveness and efficiency of our method, and we obtain a 7.01% lift in Gross Merchandise Volume, a 7.42% lift in Return on Investment, and a 3.26% lift in ad buy count.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 44 references that are in the map. First posted on arXiv 5 Mar 2024.
Builds on
14 of 44 references.
References · 14
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2017Deep Interest Network for Click-Through Rate Predictioncited by 544
- 2018Deep Interest Evolution Network for Click-Through Rate Predictioncited by 338
- 2018Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Ratecited by 173
- 2017Real-Time Bidding by Reinforcement Learning in Display Advertisingcited by 91
- 2018Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertisingcited by 59
- 2022ESCM2: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimationcited by 47
- 2016Display Advertising with Real-Time Bidding (RTB) and Behavioural Targetingcited by 42
- 2019Large-scale Causal Approaches to Debiasing Post-click Conversion Rate Estimation with Multi-task Learningcited by 39
- 2013Real-time Bidding for Online Advertising: Measurement and Analysiscited by 32
- 2018Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Taskscited by 24
- 2021An Efficient Deep Distribution Network for Bid Shading in First-Price Auctionscited by 14
2 more
Built on by
Citing papers per year: 2024: 1; 2025: 2.
3 papers.