Abstract:
This paper presents a production-grade, real-time optimization framework for ad serving in retailer
media platforms, integrating three complementary machine learning systems: (i) a gradient-boosted
bid optimization model, (ii) deep neural networks for click-through rate (CTR) and conversion rate
(CVR) prediction, and (iii) a Bayesian multi-armed bandit for adaptive creative selection.
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