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arXiv Machine Learning By Yichu Zhou, Qinyi Chen, Fei Feng, Jacob Loh, Mehdi Ben Ayed, Lin Yang, Andrei Curelea, Jiajing Xu

Reinforcement Learning for Controller Parameters in the Auto-Bidding System at Pinterest

Read the original on arXiv Machine Learning →

Pinterest’s new system, RLBP, combines reinforcement learning with traditional PID controllers to tune bidding parameters for each campaign daily. The hybrid architecture uses a multi‑head Q‑network trained on a relative‑lift reward to adapt the cost‑delivery trade‑off without retraining. Online A/B tests and post‑rollout measurements show a statistically significant drop in effective cost‑per‑click with no revenue loss.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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