Reinforcement Learning in Pinterest Ads – DRL-PUT in action!
Can the effectiveness of an advertising system be improved by almost 10% simply by tuning the weights in the ranking function more intelligently? It turns out the answer is yes – and that’s exactly what the paper Deep Reinforcement Learning for Ranking Utility Tuning in the Ad Recommender System at Pinterest (arXiv:2509.05292) is about. Traditionally, ad ranking relies on a utility function – a linear combination of multiple model predictions, such as CTR (click-through rate), conversion probability, or other business metrics. The problem? The weights of these predictors were historically tuned manually by engineers. This approach: ...