Ad Auction

Ad auctions are automated systems allocating online advertisements, primarily aiming to maximize revenue for platforms while ensuring fair competition among advertisers. Current research focuses on improving auction mechanisms through advanced machine learning techniques, such as incorporating deep neural networks for click-through rate prediction and developing novel algorithms like adaptive importance sampling for efficient optimization and primal-dual methods leveraging machine learning predictions. These advancements enhance the efficiency and fairness of ad allocation, impacting both platform revenue and advertiser performance, with implications for the broader fields of mechanism design, online learning, and AI.