# Do not Waste Money on Advertising Spend: Bid Recommendation via Concavity Changes

arXiv: https://arxiv.org/abs/2212.13923 · HTML: https://mlsanity.com/paper/2212.13923/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 29 references that are in the map.
- First posted on arXiv 26 Dec 2022.

## Builds on (most cited first, 8 of 8)

- [Real-Time Bidding by Reinforcement Learning in Display Advertising](https://mlsanity.com/paper/1701.02490/) (2017)
- [Optimized Cost per Click in Taobao Display Advertising](https://mlsanity.com/paper/1703.02091/) (2017)
- [Feedback Control of Real-Time Display Advertising](https://mlsanity.com/paper/1603.01055/) (2016)
- [Profit Maximization for Online Advertising Demand-Side Platforms](https://mlsanity.com/paper/1706.01614/) (2017)
- [Lift-Based Bidding in Ad Selection](https://mlsanity.com/paper/1507.04811/) (2015)
- [Optimal Real-Time Bidding Strategies](https://mlsanity.com/paper/1511.08409/) (2015)
- [A Field Guide to Personalized Reserve Prices](https://mlsanity.com/paper/1602.07720/) (2016)
- [Managing Risk of Bidding in Display Advertising](https://mlsanity.com/paper/1701.02433/) (2017)

## Built on by (most cited first, 1 of 1)

- [Autobidding Arena: unified evaluation of the classical and RL-based autobidding algorithms](https://mlsanity.com/paper/2510.19357/) (2025)

## Abstract (arXiv)

In computational advertising, a challenging problem is how to recommend the bid for advertisers to achieve the best return on investment (ROI) given budget constraint. This paper presents a bid recommendation scenario that discovers the concavity changes in click prediction curves. The recommended bid is derived based on the turning point from significant increase (i.e. concave downward) to slow increase (convex upward). Parametric learning based method is applied by solving the corresponding constraint optimization problem. Empirical studies on real-world advertising scenarios clearly demonstrate the performance gains for business metrics (including revenue increase, click increase and advertiser ROI increase).